{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 单变量房价预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "sns.set(context=\"notebook\", style=\"whitegrid\", palette=\"dark\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x120c64c88>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df0 = pd.read_csv('data0.csv', names=['square', 'price'])\n",
    "sns.lmplot('square', 'price', df0, height=6, fit_reg=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 47 entries, 0 to 46\n",
      "Data columns (total 2 columns):\n",
      "square    47 non-null int64\n",
      "price     47 non-null int64\n",
      "dtypes: int64(2)\n",
      "memory usage: 832.0 bytes\n"
     ]
    }
   ],
   "source": [
    "df0.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 多变量房价预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>square</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2104</td>\n",
       "      <td>3</td>\n",
       "      <td>399900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1600</td>\n",
       "      <td>3</td>\n",
       "      <td>329900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2400</td>\n",
       "      <td>3</td>\n",
       "      <td>369000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1416</td>\n",
       "      <td>2</td>\n",
       "      <td>232000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3000</td>\n",
       "      <td>4</td>\n",
       "      <td>539900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   square  bedrooms   price\n",
       "0    2104         3  399900\n",
       "1    1600         3  329900\n",
       "2    2400         3  369000\n",
       "3    1416         2  232000\n",
       "4    3000         4  539900"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from mpl_toolkits import mplot3d\n",
    "\n",
    "df1 = pd.read_csv('data1.csv', names=['square', 'bedrooms', 'price'])\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<mpl_toolkits.mplot3d.art3d.Path3DCollection at 0x122f43400>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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hU5/6FAAPP/wwQG5xcfEq4APA/+k+316kWwf1ChpElNvq4rRt2+m5tby8XNHCvBG8Rq/tHCvmKRZUsVgkFouRz+crjHHEsZ1MWex2CDKWJMlZ0FCrX62u7KpXfdeNG8rFJslOj3ds5RSWbRMOlFNC0VCETCFLLJ1kdnSq4ZjuNMX8/Dxf/OIXOXr0KJOTk8RisYqqto997GPcfffdLC0tsXfvXqd56e23386RI0eYn5+nWCxy7bXXAvAbv/EbPPTQQ7zlLW/hmWee4fOf/7zz+tvf/nbuuecennzySb7yla8A8MY3vpH77rsPXdd58sknAb4CsLi4+L2FhYXRhYWFPYuLi6ehR7oVELIv0zRrChpaKRJEqa5QI0iSxBVXXNHW5pgXtEOQkiSRz+dJJBIUCgVGR0eZnZ2te/H2SLcSjcpsG+lXq03L3daMgUAAXdcpFAr4fL4ta4x3Q6Tbznjjg6OYlunkYzWj7FQ2FL1QeemFyMUaGhoaYmZmxnn96aefplgscsstt/DYY48xNjZ24bPHx1ldXSUWi1W8PjY2xurqKqlUyik9dr8OVLzH5/MRjUZZW1sjFosBuKuYVoBZoEe6Am6NrVsD6b5wGhGjKNVNJBLIssz4+DiRSITnn3++rTLNdkjXy7FCK7m0tFTXhax6zItJurudzJtpjN3a1VwuRzqdruk63KgFfCPs9Ei3XQnavolZ7rr17Xzp//5bR3Xz8Xf8EZFg2BnPyxzF5nZ1+u6rX/0q73rXu5yxqtHo+mv2eiM0maOzaF/SpFuPbBt9aaKIQcDdwlxVVaampohEIhWP9V4v5nbkXa2OFfnHYrGIJEns37+/qfYXdj/pCey0c3DL2tbW1piYmCAQCFT0VhOVXUJjXC2VEjv01VVXOz3SbZfE//D23+FXr30NZ5KrHJjay76JC4VFXotBRDDiVt9omsYzzzzDpz/9aQAmJiZIJBLOv8diMcbHx2tej8fjjI+PMzw8TDabdaJw8TqUo+REIsHk5CSGYZDNZhkcHGR8fJyTJ09OAi+eH24KOCvGfkmSrm3bFItFMpmMs4nU6iJRFAVd1zFN0/FFEC3MI5FIzfHtEulWc7q5XI5YLIamaU4e+ejRox3dIGtWEXexNsOqsVM3q9xo1FvNNM0KMhayNqCChLvR5PJiqxcArpyb58q5+ZrXTdP0rNGFymhzcXGRffv2OaqVl7/85Zw4cYJTp04xOzvLY489xm/+5m8yMzNDIBDg3/7t37j++ut55JFHuOmmm1BVlYMHD3L48GFuv/1253WAQ4cO8cgjj3DXXXdx+PBhDh48iKqqHDp0iB/+8IfvBH6wsLBwI1AU+Vx4iZGuu6BBbCx59bGFMrG98MILNS3M66EbMjCoJchqsh0cHKxou9LJtEG3SOhSibSbwQuJK4pCOByukbWJluqiFDqfz6PrOseOHeuIdWanCwq6sTHnZX6CnN3f89LSEpOTk87/DwQCfPrTn+a9730vpVKJQ4cOcfPNNwPwwAMPcO+995LL5bj66qt55zvfCcBHP/pRPvShD/HFL36Rqakp/uzP/gyA97///XzoQx/itttuo6+vjwceeACAd7zjHXzuc58LLCws/AdQAt7hnudLgnTrFTT4fD5PRCd8Y9fW1lAUpWWprkA3NsfEuKZpks1mHX9dQbb1os9O52qry5Btu+zDura25mwatWsDuBOxU8qAxbXq1hin02ny+Tyjo6MOGdcrsfVa8NGN9EKrSr92x9tsNdqtt97KrbfeWvHaDTfcwD/+4z/WvP/KK6/kG9/4Rs3rMzMzQgZWgcHBQb70pS/VvB4IBFhcXPydRvO8pEm3WUGDoihNnZCqS3UnJycdk2cv6IYMTEiWMpkMkiQ1JNt2x90M6dq27RC/ZVkMDAxgmia5XM7pVnCx3ME6hU7nTTs5lizLjlzKnd6q5wRW7ZFb/Xtc7I20VvA6P69piIuNS450BSFUd2hoVKpbfZcvlUrE43EymYzjrqWqqpNM94pOkq6b4DRNIxKJMDc315IUuhHpirkkEgksy2J8fJy+vj50Xa/Z7Kl2ByuVShU792Lxi3EvdWxHvtkta6vnBCZ+D3crHyibL+m63pGb48XS/e4G3wW4hEi3XkFDsx1PsXkmfqhCoUAikSCbzTIyMlLjQeDVOUyg3fRCIzlaJpMhHo87BFcsFp33eBm3k6SbzWaxbZvV1VXGx8cZGBioeK+bDBq5g1XnJ8Vm0ZkzZ5zj3ZHYxYpcdrIWdjNjucm4Wta2vLxMKBRytOaNrDNFx2EvKoKLFen2SHcb4C5oOHHiBLOzs571jrIsO674onjAXalVfWy3SLdajibI9rzImrGxMacnmlgQXtAp0hWbdbquI8sy+/btqygQEDc3L5+lKErNzv2pU6cYHh5GluUac2z3I3G3K726iYtNuo0gNp4ikUjFBl4960xN02o0xm63NjGnTpNuO+qFTuaSu4WdP8MGqKexFSkFL6W6uVwO0zQ5e/YsY2NjTYsHoPukK1IdoqoNcB7dq4s0Oi1Fa0SY+Xye1dVVNE1jfHycwcFBXnjhBU+f3Q5EG5ZwOFw3PymiYuGGVi8K85prvxSwHRVk9awzofJJRRR9uDXGgUDA+Xcv1ple5+fVwLwX6XYBzQoaWm2OuR/XTdPE5/M11NlWo5ukC2UjmhdffNGpamtkQtNu9dpmIl1RYFEqlRgbG2NoaMiZy3bKu5o9EldLqMTCtyyL1dXVTbWCd2Onpxcu1sZXvScVqNQYZzIZNjY2SCaTzm9YHRm385u0Y2Dei3S7ANM0nU2b6gul+jFdwLZt0uk08Xjc2fXv7+/n5MmTm4pGO+WnIOYVi8WwbZvZ2Vmi0WjLMsN2lQZejysUCqyurlIsFp3IdrM+Dd1EoyisVCqxtLSE3++vsGl0S6jEH1VVty1fvFPkZ90cz60xXltbY3p6Gp/PV0HG1ZaM1UTcKIff20i7yJBlueEPUL3ZJUp1E4kEPp+PycnJClJrZ3OseuPNyzwbjS38GuLxOD6fj+HhYXK5XEU012wenfZpEI/sp06d8uSK1ml0ishFuezQ0JDzWrWEyr1r75a0iYUvNoo6LfGCnVst162NL7fGuDpt5O4cUd3gspqM28np9kh3myHSC5ZVbmEej8cJBoPMzMwQDocbysa8ol3SFXIcAUG2sVgMVVWd1ur5fJ5sNut5Dp3yaRBVeblcDoArrrii5cW9EyLddtBIQlUtaXNvFImUhGma5PP5juQmd1pk2q3xvHiOSFLjNj7uG6TQfIv/n8lkmlpn9tQLFwGSJLGxsUEsFiMcDrNnz56KHdlqtMoBV2Oz2lu3OY7f76/JI3cjehXH1iNIt7fu6OgoU1NTHD161FM0sdtItxFaSdqy2SyFQoFkMum09XFHYM2qvDZKOQzTYCjUX1PB1wns5EjXqzlNPTS6QZ48eZLh4WEkSarZUFVVlbW1Nf7pn/6J/v5+Xv3qV3PttdcyPj7OE088wV/+5V+Sz+e58cYbuffee3n66ae73jXiT/7kT/jHf/zH56jTNQJ2IenW+zENwyCZTJJKpfD7/exr0MK8GtshA0smkyQSCQKBQMfMcTab0y2VSsRiMbLZbIW3rshVb2bMTmGnELnYKILyhuLc3JzzOOyu8qonafP7/fzVTx7l20d/gCRJ/OLkFXzkV+8iqHRW4tZJl7GdnvoQYwaDwYYbqpqmsbGxwY9+9CP+/u//HsMwOHjwIKdPn+brX/86IyMj/M7v/A5PPfUUH/3oR3n44YeZmpriD/7gD3jqqac4dOgQ99xzD5/85Ce59tpr+fCHP8zXvvY17rzzTqdrxG233cbnP/95vvCFL3DPPfc4XSO+/OUv88gjj/CpT32KBx98kIcffphQKMTi4uJVCwsLN1HuGvFq9/ns/Jq5JtB1nZWVFY4ePYphGIyOjhKJRDwRLmwu0vVyvGjVk8lkyGQyzM3NsW/fvoYqiW75NIiouFQqsby8zPHjx50WPWNjYzXGOO1UpdX7rM1ip2pu3YoNUW47PDzM1NQUe/fuZX5+nunpafr7+wE4/PPv8ch//DNBVMKSn2dP/4y/+P5XHG/jTt1YOklsF7trxFbGFBuqV1xxBffffz+f/exn+dd//Vcee+wxrr32Wm699VYmJydRVZU///M/JxQKOV0jfD6f0zXizJkzNV0jjhw5gq7rPPPMM7zhDW+oeB3gySef5PbbbwfKXSO+973vOV0j3vSmNwHlrhHA6MLCwh73vHdlpFsqlUgkEmxsbDA4OOiU6q6vr5PJZDyP1W6k22rjzbIs1tbWSCQSjvnLvn37OjqPdo61LItMJkMqlarbEFPAbV7TqdLilwJEykGYl8dfSBMKBImEIliWRRSb5+LHnW7P1a5gm5FPQWclYzs5VdHOmCIYCoVCXH755WSzWVRV5fd+7/eIx+O89rWv5fLLL9+WrhHusajqGgG7kHRtu9wZtL+/v6ZUdzPpgk7kdN1kGw6H2bt3L7Zts7KyUmeUWmzGcKYZNE0jHo+zvr7uRLatFnY78rJuYKcR+WbIaHZgEsMyARtFkdFsnfnxvUxOTnLmzBnm5uYq5FPpdLrujr3470afv1Or26A7XSi8zFGsS3Gdm6bJs88+y8MPP0w4HOYP//AP61qxNrrum73eCF66RsAuJF1Jkrj88svr/lu76YKt+imYpumQbSQSqcgle+0S6x7Xy8XV7MYiyHZjY4Ph4WEmJiYcnWordMMcxyt2anqhXdy68Mv8f6d/wk/PvYAsyYxHhrnr1W91vq9G8qlmkrZqMvb5fDs+vdANEm81ZrWX7ujoKDfccIPTWPR1r3sdR44cqVgL3eoaEY/H2bt3rxiuomsE7ELShcYLv5tqBPfxYoMsmUwSjUbZv39/TR65XZWB113ueueu6zrxeJx0Os3Q0JDzBJBKpbpevXapYjPnGPD5uf8N7+do8jSGaXBgZI6QGnTUD/XQTNLmbnYpNu7EzXltbY1QKOSQ8WalUt1QVnTad8FrCbD7c1/72tfywQ9+kI2NDSKRCN///ve5+eab+fKXv9z1rhGPPvooBw8epF7XCLjESLfddEG7JA043gjRaLSpoXm7hO6VzNzj6rpOIpFgfX2dwcHBuumWblWvCQi/iFgsVpHj3EoJ7k7BZshIkRWuHNtf8dpmiK2Z98HJkyfx+/1Oya27wsurcbnATt9I22w12stf/nLe/e53c+edd6LrOq95zWv4rd/6LS677LKud434yEc+QqOuEbBLSbcRumW/KCRpa2tr+P1+T90j2iE891y85F4BVlZWHLIVG4n1ju2GFEzk2YQTmiitBirakIvURrVlY3W+8lKPnjsZTYqqu4GBAec3r1fh5TYur05RuO0Zd3pOdyu2jnfccQd33HFHxWvb0TXiM5/5DJ/5zGeuaTTXXUm6jS6Sdv0RWkW6olVPKpWiv7+fsbExdF1vq11PJ70axHygfDE2IluBdsjM601CqEeOHz+OZVlMTEzQ19fn+BhX9/cSVV8iKnO7hAkScHsg7xTs5JtA9TXVrMLL7QhW7ZUbCAScCjLDMGq6Dm8GOyXS3cnYlaTbCMIfQTiItUIjYqwm2wMHDuD3+1lfX3e6s3qZSzvVSM1I1z2fgYEBZFlmYmKi5Tl2onrNDVGubNs2U1NTjom5eH+9MUVk64bQDgsyEBuAyWSyIirebmOaevPvBC5WRZo75eCG+/vPZrPous6pU6ewbbsmRdGukXy3NtJaYbeUAMMuJd1mP+pWTGzcOdKBgQGHbAU2u/G22fJa0zSdpphu8s9kMp7m0amcbqFQIBaLUSwW8fv99Pf3Mzg46GncRvNy2wNalkUwGCQSiThkUN1rrZqMOxGVdRIlQ+Mbi9/hvydeYDDQz9uuuoV9AzPAzvNKqP7+fT4fExMTNY5g1ZK26nxxvTnYtt1R8mvH7Ga3eCrvStJths0oGIQzfqscaad0va2Odasj+vr6asi/G0qDeseKsuFcLucYvQtxeKfhfkSut4tfzzu3mog7rQ9th9j+9uf/xH9b+SmDgT7OZFf582f/ho/+pz9kODTQcceybnjzSlJjRzB3iiibzZJMJh3fg2oyNk3Tk/etV1xqBuZwCZLZ8l7qAAAgAElEQVRuO8QoJDgnTpyoaELZbOxuejUYhkEsFnPIttGG3VY7QrQ6VtM0YrEYmUymbgujRmN2o+6+3i6+bdtOVFbthWDbNmfPnq0gY6/tmzYLy7Z45tzPGA0NIksyfkUlUVjn2PpphkMvAzqvRd6u1EezFFF1Ox/ReLRQKDidI7YqaeuR7g7BVtML7iICWZYr6ueboVvqCOFsdfbs2aZkK9BOpNtOqsUwDM6ePUs6nWZ4eLhuJVu3iiPaGbNRVCZyk9FotEbbWm1i3qr8tq35IBGQVQzLxK+cT+nY4FcudDruZDHDTlAbNJK0iSaX4gmyE5I2r10jeqR7kdAsveAmW1FEsLS05Pmi63SkK8qH4/E4siwzOjrqVLw0g1cy9UpmwkHr7NmzFcUVjcbcqRCbl9U3UHdU7M5VVje9NBWbH6eeJ2vkmFJGmZJHPH/uW668mYf/oyxFsrA5MDDH1SMHgJ1dttvpYgbbtgmFQjUqllaSNjcZuyVt7agXdkOrnoWFhaGdP8s6aBXpVpNuqVQiHo+TyWQYHh6uIJV2csCdIt1qr4b9+/eztrbm+U7tdYOs1XHu3LFQRIyMNCea3aipdbeSEXDnKkulEvH1BH+//Dg/jx/jZOIcFja37nsNdw/+jqfH4xtnX8FYeJhjqdP0B6K8cuoXUJXOL69u6Go7mYOtN792JG0iRSEIuFQqoapqU0mbkL3tZNJdWFjwA/8ZeOvOneUm4c7pVpNtvcflzWx2bVYG5u5oIWzmxA5yu/aOW4l03RG2qKyLxWKePRq6oandbiJ35yr7+vpYTa1zInOW/zhzAuv8ZtXXn/9/mY/Mcf3IlY7peTNTmoXhfSwM76v5rG5sfHUKF7M4opGkzd1xOJfLkc1mWV9fd36z6t9BrPedSLoLCwvy4uKiBbwduB64dufNcotQFIVCocDS0hLZbLappaE43mukKx5f22nZY1lWU7J1j92NQgb3caKDheis4faM2KoiYisLdyekLCzb4kTsDJZtocgKNmCYJt+L/5i3vuo25/FYaFvFDn49Eqhe/LslvXA2E+NLP/p7zmUTXDM6z7uvu4OIWuvM1QydKI5wdxxeX19namrK6ZVWnSb6wQ9+wF/8xV8wNTXFy172Mq688kpe97rXcd9995FMJp3f4r777uP06dN88YtfRNd1fvd3f5ff/u3fBuhKN4njx49/D3grED9/Wv8D8GfA2V1Juo0uOvFDiG621bvu9bBZT12vUWE2myUejxMIBJq2D2pHddFupGtZltN1OBAIbJn0d1t6wQv2RWfwK35sbGzAti1kSSJwvuuDFzlbLperaO0jyFioKjqBbkSmkiSR1fJ86Ik/Y0PLosoq3z31r8Tza3zi0Pva+rxuVaQ12jydnp5mcnKSn/zkJ2SzWY4cOUIikeD48eM8+eSTDumurq5y9913881vfhO/38/b3vY2Xv3qVzM7O8uHP/zhjneTWFhY+K/AfwHuPD9VFTCB2V1JulBJEoVCgXg8Tj6fJxKJoChKtZFwQwiplld4IWnbth3dr6IozM3NNe3VJsatbmTZ7Nh2FvGLL76Iz+dr2C4ILq6f7k7IE/f5I/xvN76Huw9/Bs3UkZAI+4K86xX/ueF7GsnZqlv75PN5TNOkWCzWbBq1K2frVqHF88kT5PUCEbV8naqyj58ljpLTC0T9za9dN7ZbXaGqKjfccANzc3O84hWvQJIkjh07xpEjR3jPe95DMpnkrW99K5FIhF/6pV9yinre8IY3cOTIEV71qlc53SQAp5vE/Px8TTeJhx56iLe85S0888wzfP7zn3def/vb384999zDk08+yVe+8hUxtf8L+Dzl7jwm8A3Kke9tu5Z04UKlVKFQcHp+5fN54vF46zefh6IoaJrm+fhmpCvINhaL4ff7GRgYcDZxWqFdeVezY23bJpvNOoUMExMT9Pf3t9RjXorWjoZlYNgGATnQkgxunHsFf/Mb9/Otn/8zxVKBN+y5gZdN1PdubgR3VCxucGtraxiGQX9/f4VVY3WRh5fS227lYFVFxeJC4YVNWfbmk71ThLguOplK8do1QqT+oOwEeMMNN/Cxj32MYrHIO9/5Tm655ZaarhE//elPazo9dKqbxOLiorGwsLABjAFnFxcXv7qwsBAGfrxrSXd5eZlMJuNUSokfplt9z9zHVxOebdvO47vP52NmZoZoNOp0kvU6bidyurlcjtXVVUzTZHx8nDNnzhCJRFouhEuRdF9Iv8iP1n6KbVuMBEa4ceIGQr7m/fOuGruMqw5dRiqVautm3Awib1pP1+qWUq2mEyytrzDk62M4PFCjK1ZVtWuR7tWjl3FgcI4X1k4C5d/5TVf8KkGfv/kALng1HG93bq3Gq/ZduO6667juuusACIfD3HHHHdx///3cddddFe9rtj/R7utNYAEsLCwEKed337ZrSVe0Dq++C27GU3ezLX4E2cbjcRRFYXp6uoLgutX7rF6km8/nicVilEolxsfHGRwcRJIkzp0711FNb6PjisUixWKRUCi0KV+EThN5vJjk2eSP6Ff7USSZZGmNZ5P/zi9P/CfPY3SSPBpB5Cm/f/ZH/Ol3H8InKxiWyb033sVrRw6iaRrpdNqRUonOEaIV02Z6rLkhiNIn+/jkr7yfI8d+wEo2ztWjB/jlues3NVan0I7vgvs7ePbZZ9F1nRtuuAEof/8zMzMV3SEadY3oVDeJhYUFH9APJM8PcS9wHfD/7FrSDYfDdcm1W1Vj7uNN03QiW1mWmZycJBqN1izSbsjA3HOAMtnFYjHy+bxDtu4L1XOBhG1yOrfMqpJkOjLJSHCo4Tzd47nbuvv9fmKxGECNL0Kznl/dyBNvaBtISPjk8mLsU6PECt7TTp1Gs3NMFTb40+8+RNG4EFl/8gdf4pff+V8Z7R91XjNNk1QqRTabbepZXF1g0AzuyDmg+HnzFb+66XPsxiaalxtKNTlnMhkeeughvvrVr6LrOt/61rf43Oc+xz333ON03PjOd77DJz7xCRYWFjhx4kTHu0kA/yPw/cXFRbFR81bgasDetaTbCCK90ClPXTdEzf/q6io+n68h2Qq0S6Tt+CQYhuHI4sbGxpidna17wXshXc3U+Xbsu8SLawQyfhRJ4Tcvu43Z6HTD97hbBI2MjDA5Oenk1tzSHrdbWHUpbqc7S7jPM+QLlZUI56+DgllkwN+61LveWJ2YVzMyOpuJnc+dXiBdn+zjzMYqw6EB5zVFUZzvcGJiwhnbXeSRyWRIJBI1nsWNvu9OEuXFKlGuJufXvva1/OQnP+HXf/3XsSyLO++8k+uvv567776bd77znei6zh133MEv/uIvAvDpT3+6490kgD8EfhvgfC7XXFxcNOASLAOWpEq7xlbwqkYQXRJ0Xaevr4+ZmZmWF1g30gu6rpNOpykUCoyNjbWUxXkh3aPp4yRKawyqfYSCYfJ6nifO/gvvuOItNcfatk2xWOTFF1+saBFkWZZDuvWkPW4PV6F1LZVKTg7QTSheo7RmmAyNM993GccyJ5CQCSh+XjXa3uPydmlrp/vGMaxKBY1hGcz0T7Qcq7rIQ6DR9+2WswUCgY4WunS6cGMrBuYf+MAH+MAHPlDx2u23387tt99e8/4udZN4jeufbOC7CwsLfwM8tmtJt9lFLB6/vZBus0hXqABisZjTJSGfz3veLOgk6RqG4bRVD4fDRKNRTz4NXuZQMkvnd6zLUBWVglGsOEZUsYmUSrXdpJd5uD1c4YK8Kh6PYxhGRWeD6gitXetGWZJ55egruLz/AIZtMKD2OwY0Ow1DoX4+/tr/hY8+8Zf4ZB+6ZfCxX/mfK6JcAa/RZLPv203EAMePH++IZ/HF7BrRyVLmTmNxcbGwsLDwEeBzwO/tWtJthnbyuvVKe6vJdnx83JFciXYzXsduJ2VQb85uI/OBgQHm5+cpFAqkUinP47aaw0xkqnxuZgm/5WejlOH68fKjl1sGFwwGmZycJJ1Ot0W49WBYBkeWn+LHaz8Hw+Y1w9fz2j2vcc65kUFNNTE007lKksRQYHNm69tdRXbrFTfxS3Mv58zGKtN944yE6897K/OqLvKwLItjx45x4MCBhkUe9dzZGhHhxSJdr51ithsLCwsDwDRw/Pzff8xuL45ohM2W9sqyTC6XIxaLYRgG4+PjFS1poP3otR0zHTc5NjMyLxaLHW3DMxEe4/UTh/j+6n+jZGpcO/YLvGbiVWxsbLC6ulpR4CHa9WwVT678K88mfkKf2kfJLPHdxNPMjc4w37+voUGNmxjq6VzFzn6nF/9W4ZUoh0MDdaPbzYzVzry8ehYLZzBVVWvIWKSYdoJ6YQfhMuCVQAq4D1gHiruWdJthM7Ixdz19PbJ1H9uNzTG3T4NwIItEInW9dTsRQVdjX3SOEXuQubk5crkcp0+exrbtms3CTul0F9PHCCkhFElGlX0UTYljG6eY79/X8DzqmaO4H5cLhYITvdV7XG4nGur0Rlonx+oU6TYjyUa5+WY3P1mWURTFkbNttZvHJWBgfho4R7lA4hjwY2DkkiTddogxl8thmibnzp2r0Lc2Qre0t1C+oI8ePUowGKzrjyDQLXMcwzA4efIkpVKJiYmJujeeTi34PjVCqpQmcD7PamETVeuXKAvYts2LGydYyp2lX+3j5SPXoLqIQdd1Tp8+zf79+1t6Imy3lK2T0WmnCGYzBN7o5meappObb+ZZ3M5GaTsG5jsxvbC4uJgEWFhYeH35/y7+Lexi9cJW0wvuYoJWvgRutKu9te3mPa3c1WyAU83W6Tk0g6ZpJJNJCoUCk5OT7Nmzp2kE1InI7fUzh/g/jn6NDS2DYRoMqwO8YuQXmr7n6diz/POZ75cNabD576nneOf8W1DkWrvORp4IzZzC3H86iZ3qMtbJdICiKI4CZXh4GKiVs7n9cuuVPm9GzibSSTsx0l1YWFAWFxdNIAK8bmFh4RmgsGtJtxmapRfcZDs2Nsbg4KDTfnqrY1ejmXxNyNBWV1edlkFLS0s1ZaKNxm0nvdDoWNGTLZ1OOymErZiYt0MGk+Ex/qer3sGJzDLFXIFZ/0TTEl3TNnni7L8Q9oXK1ou2zXJuhZPZJQ64UhLNotZGTmFuaVUmk3FKt0WOuN0IrRo7lXS74ePgjkwbydncfrnu77y667BhGC3nJ67FnUi64AiCSsAc8L8CS7uWdNuNdN3mOGNjYxXR3HZ0jxAXhW3bjj+CbdtMTEzQ19dXQdCdnEO9nK5bESG0tsVi0ZNRUCe9Fwb8/Vw7cjUpOdXSYc2yLUzbRJZkZx6SJKFb3h3i6qGRtEr8PkDdCK1bXYhbYaeTrpfvwu2X656LrusOGWezWQqFgqPUqefOBjhKoh2aXhAL7wfAtcDrgJt23kzbQCMCcDuHuctkq81xBNohsa2UGQuyNQyjrvNXN0xn3Dldd8eIakVEO2M2Oq7Ti9gNVVa5fOAyjqaPE/IF0Uwdv+JnNjLV8c8SxRqKojiPyrB5KdtOJcpuSLy2ImcTUbF4Ejl16hSjo6PIslxBxiI//8ILL/D4448zOTlJPB7nmmuuYWZmBlmW+cxnPkMqleLTn/70lszIh4eHefDBBxkbG0PTNP7kT/6En/3sZwSDQR544AEOHDiAbdt89rOf5YknnkCWZT7xiU9w/fXXs7CwIC0uLtqUVQz9wM+BHXh76AAE6Z4+fZp8Pu/YPja6wLod6RYKBVZWVmrMaDY79mYi3VQq5Wht3R0j3Mdt1U93KwvOy2f/xr5b+c7ykxzPnGY8OMqtc69rufm2WdQjt81K2XRdR9f1jpDcTiVwMV6nSVzI0+oVeRSLRaLRKD/+8Y85fPgw+Xyed7/73dx4441861vf4ld+5VcAtmRG/sgjj/CpT32KBx98kIcffphQKMS3v/1tnnnmGT70oQ/x9a9/nccff5xjx45x+PBhTp06xe///u9z+vRpH+X0ggl8EPi7xcXFL8Mu3khrhGKx6GwKjY+PNyVbgW71SSsWi+i6zsrKCuPj4003qNqZh5cNOrhACNlslkAg0DET803Y23UEQSXAm/a+oeuf0w68SNlM03SeMDohZdvJke52jCfy89dccw0f/OAHOXfuHNdee63T2fuP/uiPuOuuu3j++ec5c+bMlszI3/jGN3Lfffeh6zpPPvkk73//+wF45StfSSqV4uzZszz11FPceuutyLLM/v37mZ6e5vTp0/8J+P75KZ8Dvivmv6tJ100AbrergYEBLMvqSvcIkUtsdvFrmkYsFiOTyaAoiiO/8jK2V9JtNQeRyiiVSoTDYfbs2dMySt2tfrqGpaPZJUzLOt9sZ+vY6jm6Na7ClCgQCGxZyraTI92LQeLiGFmW2bt3L+973/u4++67WVlZAdiyGbnP5yMajTol8NVjnTt3zrGDdL8OzLqmGQb+cmFh4e+AM7uadKGy4+/IyAjT09MYhuHUlXvBZrpH1KuWcTtvie7DZ86caWvcraoSisUiq6urTp84sVPcanG1Q/j1Pner0p3NklzRLHCmtIRtW5iWScmnd4xMtqvyqx0p20sl0vXyJAeVBuZf//rXmZqa4oYbbuCb3/ymM041NvO01ui8mqxZ63w+F+BHwE2U7R2lXU268XicWCxW015dVHZ5xWYVCQKGYZBIJEilUhXOW+2OvZlcrThnd3Tt3jBcW1vreARbfVw+n2dlZYVCoYDP5yMYDNbdVNIsjdO5UxTNImOBMSZCk85nbxYxbRUZCVUJYdgGG74NClaOsNJc67ydaEYe7UrZbNsmkUgQDod3lJRNzLmTNpFejKXca+Dw4cPE43He/OY3k06nyefzSJK0JTNyEcANDg4yPj5OPB5n7969FWNNTExUKH/O//dZ1zT/d+CTgB9QdzXp9vf3MzAwUJMTa7dlz2aOF1aG1WY01RU03SJdcYd1u49V33zAO5m2U7kmUCqVWF1ddfLnoVDIidqKxWLFppIaUHnO/jkFCiiywvHcMV42+HL2R/Z7Ot9G0G0NVVKduUm2hGl7/y0b4WKnUBpJ2U6ePOmY1Qgpm2VZdaNiL4/mnfYz7hSJe/VdcEe6f/3Xf+28/s1vfpMf/vCH3H///bzxjW/ctBn54cOHOXjwIKqqcujQIR599FEOHjzIs88+SyAQYHp6mptuuol/+Id/4I1vfCPLy8ucPHkS4Bkxl8XFRdGzS4ddntMVi7wa4of3eudtN9KVJIm1tTU2NjZqpFdbGbvdoodEIkE6nWZgYKAiuq4+rhvtes6ePUs6nXaUIZIkoWlaXTG8YRgsZU5TSOfxE8DSTQzb5EfFfycUCTnHbCZSishRsuYGATmIdZ5s/XJnKsp2Wu5UjBGJRCo27naKlK3TqY9O+S5sxYy8r6+PBx54AIB3vOMdfOQjH+G2227D7/fz2c9+FoCbb76Zn/70p7zpTW8C4FOf+hQ33nhjodF8pBYLbWftmFTBNM2GG2DPPfdcQyKqRrFYZGlpicsvb975VUivzp07RygUYnp6umUFmbsjbyucO3euZft4MYeVlRWi0SjT09NNbRY3NjZIpVLOI1GzcZ977jmuueaapsckEgknpTM+Pu58v0Ip0WjRnckv8+/r/07UV36ENi2TgpHnxshNjvbStu2G6Qk3NKtE2khhYuKXAhSMAgUrh23ZGEmbq/Zd3fRcvUD8xl42QFvh+PHjzM3NdcTz1etY1VI28cctZSuVSgSDQUZHR7dMlqZpcuLECebn57c0jkA+nyeZTDqt0RvhzJkzBAIB9u/f2hNTF9DwC93VkW4ziJSBF9JtFY3a9gVP2UAgQDgcZmhoyFPJrqIoLautvMxDeDSsrq46i2ZsbKylr20nVAm2bTs6XyE5m5ycbCsqHQmMokoqeSOPT/ZRMkvsj17G0OAQiqKQy+WYnJx0iKKg5Uln1tBSBrIpE1LCBINBfAGFnLKBT1HxST6KVoGoGmVKmcHQDZatZc9zaobd7jJWT8pWbdeYzWbRNI319fUtS9kupoH5Di0BbohdTbpbNb0RaOSnYNu24ynrNsVZXl7eUhlus3lUE7Rtlw3VV1dXkSTJmcOJEye6IvFyL2rx2SIC37NnD+FwmEwm0zaRBJUgrxm9keczz1EwCuwL7+PyvitqPjcQCODzK+hmkQEGwAbd0lH1AGbJJFFMUpTyoMuokh+f6kNTSwT8oY5rhTs53k5IVUhSpV1jsVikr6+PSCTiScoWDAYbbtrtlP5ouwG7mnSboR1jGrExJi7oaqKbmpqq8JTdTGcKL6gmyHw+z7lz5zBNs8KjQRzrNVe7Ge1vPp+vKFl2f/Zm0af28crhV9X9bAHbtsmZGUpWCb/kxyepBBQJS7GQgxC1osimDcj4LBVLtzE0nXNr59D1slxsZWWlIkVxsRflTtXWujWum5WyBYNB/H5/V6rRvJLuTvRdaIbdNdsqtIp02yE7QU6FQoHV1VWnJ1o9summIsGyrBqtbb2yYa9qg3a1v6VSiUQiQS6XY3x8nKGhoZrP7maBRMHKU7ALWJhotoZua+XNNywkWSIoBzFsHc0qYcgaoVCEKXWawGiQUqnE8vIy4XC4pvmlmySqN5Q0q0TKSKDbBkEpyJA6smOJcrvGaiRla+QQJq6zRCJR9ztuF5tRL+wW7GrSbYZ2ZWCyLHPq1KmWnSPEsd3warAsi1wuV6O1rYdOqxIMw3AkSSMjI45xiG3bFM0Clm0RVELIktwW6ZasEoalE5AD+OTGmz9i97tkFwlKIQxbJ6Ul0dEwLZNhdYw+KYokS0SVPkqSioTEsDqGT1LLLmSSCT4qjISEe5UgiXQ6TbFYdDaU1IBKIZjBp/jw+wKUrCJreqLhPC8mOn2j20xKoJFDWDqdJp1OA5BOpx0pm6iuE0TcrMda9dxakakoyOlFujsEXklXRJWmaRKNRhkbG2t5IQrXIy/wQrpCa5tKpfD5fDVa20bjdiKna1kWyWTSEZDv27fPWVCWbXGmcJqMvlGOfCQ/eyP7PZNurHSOldIyICEjsz88T9TXV3NcTRQvyWzoGxTMAgFFxbBMlnKnme+bx5ZARkKRFfrkQXySimmbZKw0Ohp22CBjpemTB5wnmEYytlKpRLaUQdM1SnmNDTNTXsBqDr8WIqAFdpRJjRink5FuJ1ICotrO7/czOjrqvO7etCsUCqyvr6NpmqfOw166RohrsBfpbiNale01Izvh1ZDL5RgdHUXX9Yq8bTNspoihHoQEK5lMMjAwwPT0NKlUytNFtNWcrluREQqFuOyyyzh58uSFqj7bIlGKk9ZShJRIOfVgFVktnmtIupZlYct2Oeq0DFaKy/jlALIkY1g6JwvHuCb68qaPtAEpSIkCBaOAKquUpy6BBKYFQ74+LGz8csApiihYOWzbwoeKZMrotuZEzI0gNpTUkIquF1Epq0A0XUM3Naf4YG1trUbvGgwGPbcnF99TJ0m3U+h0frh6LC+ubKlUimKxWLNpp+t6S3WQCKp6ke42oxEBKIridABwQ9M04vE4GxsbjleDoihkMpmueOrWI2jbth3XKXfzyXw+3xEyrz7O9OmsFJewsYkofUgFhVgshizLTpdfuPBdlswiK8VlckaGkl1EsXwElCA+yYdmlZxzcJ+PaZrEtVVSRvL8qxKWbSGdlyv6ZJWiVcDExFfnshPjheQwiq3gk1UKRg5FKndvwIaAHMAvB5GpLA+1sJCQHbMbCRnL9vY9+mU/UbmfrLVRfq8PJkMzpLLrDAwM1Ozsr6+v1yWJRjv7OzWfC533SvAyViMpm3jy0DSNXC5HoVAgn89XNLms3hgVa6VHujsE1emFemY07oiyW5667mNF7isWi+H3+2uaT7YjL/N6rGaXMEMGMgqGbnAmvYSUV5gZn6vZJBSkGyuVy8aDSpiiWaJoFVAkH4at0+cfICPlnPMRPhdZI8O6tUZQKUcnBTOPjo5qGSiSgm5pKJIPTLBky/luxOe65xCQghwIXc5PN36EZhWxsZgITRLxhyiRL8/NDiNL5d/Ph1qWkSFhn/+f2iR/XI0B3xAhO4xpm6iSiir7WbNTF+bThCSqd/arCaITBRHuz93Jke5mCdy9aSewtLTE0NCQEzyJTTtN05Blmeeee44nnniCqakpcrkcV111FX/3d3/H448/jiRJ3HHHHbzrXe/i6aef5v7776dUKnHLLbdw9913A3Td2LwZdj3pNop0Bdk1M6Opd7wXtHusaZpOPzRJkpienq7bfLIdpYHXzTzNLjp641KpRDgaJjoYpT/QX3NsmchNdEsvR7a2j6gaJatn0Owi/b4hxoITZKUTGIbh9BCTJAnD1pGQkM83iQxJEZAlTNNAx8Sn+NgbLF+MYt6maZZvRPo6GSXNWinIkH8YSZKJ+KIcHHw1WTOLjIzPJyOjICFhYVGiQIjydxiSw9iWTYEcyDYROYoqNS8aqT7vgFT7KLuZnf165bhCxladnmgXOznS7bRe1jRNJ/dbr61POp1GkiT+5V/+hW984xvous7MzAzf+c53MAyDW2+9lRtuuIEPf/jDPPzww0xNTfEHf/AHPPXUUxw6dKjrxubNsOtJtxEkSaJYLHL06FH6+/ub+iNA9xQJYqd8ZWWlbouezY7bbDNrQ09zdGMRzSwRMkNI5zeexsbGMG0DXwNzufK8JFTZj25pqLKfkBJBkXxMB+cIyuWxJElyymSFvtOnlKOUCySsMeAbZKZvz/nPVJ3+ZnDBCe5U+gQJfRWf38fZ0jIZI82UWlZtyJLCgDKILVkUyDupChkZC6NiYymiRFFNP+lsluB441xuN1Evh6nrOqdOnXJkbKLwwC1j8+oW1ulUBXSuaMPLxle74zUyMPf7/Vx33XVcdtllJBIJrr76ao4fP+6UpYuN8Y2NDfbu3euUEt9+++0cOXKE+fn5rhubT09PNzy3XU+61ReNuw+YbdscOHDAU0vtdvO0rQhaOHDl8+XH4YNWexoAACAASURBVAMHDnhSJGw12s4ZOX6YeBpN1zANE1mRGJHHGA6PYNg6siTT5xusO6Yg8snQNCuF5fP5W5uxwCQhJew4q83OzlIsFh0SSSaT5c+LWKQD6+Wurr4gE6EpFElBkWrPW9M0VlZXSPrj9AX68fv9WLZFzsphyHpZm3v+/CwMDFnDlAxkJEBBlWo3siRJcoh5q+gkwUmSVOHhUC1jc7uF1Wt8KebRyaqvneyl63U8EV37/X6uvPJKAB566CH+6q/+iptvvrnGdHx8fJzV1dVtMTa/pElXwO0PEAqFmJ2ddcwwvGAzFWz1oOs6sViMjY0Nx4FrcXGx4yW79Y61bZtTayfIFfME5PJjmS1BMpfgZeq1ZVmPHKhLgu4x/XKAufB+DNsob1rZkmMsJEpJo9FozaN1sVgkW8xSLBUw0iYnVk46Gk3xR1EUkskk2WyWodEhcr6wo0Ioa4BlFJ9CQCn/bqZlotkmfjuAYeuYtoWEDYaKLpVLpoXvajtOcduJejeHRq3Jxc0sn8+TSpW7JIsKMPH7dKIgYCfnh8VeQSvSrVdA8b73vY/3vOc93HXXXcJisQKN1liz1xuhmbF5M+x60hXSp9XVVfx+v+MPYJpmW4uwne4R9fqkuXPHQ0NDFRt1ne59Vm9M4ZGQk3P4/T5C6nnLRMtAkmQCUhCf0vzndl94EhKKfb48mtb6UEVRiEQiFT3YhBF3sVh0etcZhoEsy+VHcAv8lp+iVMAvBzBsg4DsJyhfyK/Kcjl6DRDCb5dfNy0Dvy+IbdrO92WapvNUITZbxMXfyQisXbRDRs2+Q/FUYRgGx48fb2nb2AoXyyvBC7zqkd155GPHjqFpGldddRWhUIjXv/71HDlypOLmJNrqTExMdN3YvBku3tXYISSTSdbW1piZmWH//v1OPs1NjF7Qbj5VEJRlWcTjcY4ePYppmszPzzM5OVnxY7dDuu0SdLFY5NSpU5w5c4axsTFetucXCfrCFIw8RbOAbmuMGGPOd1EwcqyWzrJaPOvIv9xjihSCuGmJOW1mgYqaflmWyWazjh5437599Pf3Y5kWajqEsW6R2chg5WyihUFy2bzjo8D5hIEgfiRQFBlFVpxOsVBeUOl0momJCee7F9afohuvYRieb8adLmjYLISZ+eDgIAMDA4RCIebn55mZmXHMzNfX1zl9+jTHjx9neXnZkUQKK8dG89qp6QWvJcBu0l1eXubee+9F0zQ0TeOf//mfedvb3saJEyc4deoUpmny2GOPcdNNNzEzM0MgEODf/u3fAOoam7tfhwvG5kBdY3Ogwti8GXZ9pDs6OlrXm0CSpLbsHdstG5YkiWQySTKZJBwOO1rbeuiGkbnwiThx4kRNyfD1I6/iRPZFDNtgODCCZZSjwYKZ4z82fkrWyIINIV+IawcPElRCFUY3fr8fVVW3vIiEaQ7AzMxMxQZTIBBw8py2vQ9d152IWAjmgXL5aCiAP+JDVdVyUYPkR0Iqa4PPE8zo6Ghdnwhxs3H/DRcUFOIGKm4uOxnuCFCkJ9z/5k5PNJOxdbrXGnSnVU8rmKbprLlDhw7xk5/8hF//9V9HURRe//rXc9tttzE8PMx73/teSqUShw4d4uabbwa6b2zeDLvaxBzKP1Ajv9rFxUX279/f0nMWLnTPveyyy5oeJ+RXS0tLhEIhpqamKsikHgQx1pOJtTtn0SIomUwiyzKXX355RVRt2zZZa8MpILBtm3gyxnj/FMv6SZbzS/jl89VXlsZEcIqr+1+GZVmk02lH/O92nnIUCh4fX0VeO5/PMzY21tTHotU4TnqiVKSklTB0g4C/vNCKxSKRSITJycm2ds7dBFzvaUiSJOfJodVv2wqizLyVibwXbGxskMvlmJqa8vwed4pHpCk0TUNRFGzbZmhoaFP+udU4ceIEMzMzntZaKxQKBeLxOHv27Gl63NLSEpFIpCPfbRfw0jMxh/aiVy/HirwpgKqqTE9PV2gIG6ETqgTRMSIejxONRpmbm2N1dbVmQ8XGBttGki9YQEqyhE4RRVEY8g9RtIpYtoUsyeT1bPmxGwOlT2KkbxAFH4qpUizUjzzdf9wyJ9M0SSaTrK+vMzQ0xNTU1Jain3paWKF3BsoyLL3I0eUX8KsqIV+YkD9MKBRq2iNMvO7+7gT56rpOIpFA13UkSaq4obvTLF7P62JXpDXqtSZusIZhVPjnVnft8Nr08mJEurvR7AZ6pOugGTEWCgXOnSv7tQqt7YkTJ7pq7yggImuxUSiq2IT+txoSErLkw7TLVWgWJj5VwcIiKAcpyDl8cpRUKYVlmfT5B7CxKFIoa3CR0dGxFYtoX5T+/gtFFO4UgOhiYVmWUyNfKBSIRCLs27evIxGPG5qmsbq6SqlUYnx8nL6+PkxMVkpLKJaNZZsUzAx2/oLLlaqqNTeJRrv+kiSRTqeJx+P09/czPz9fcTMRG3bu9ITIizbbsLvYpFsPIvXm9/udTR93lV2xWGwqY6vnFHaxSHe3md3AJUC6WzG9qT62mqDdWttqb9l287SbyenmcjlWzq1gqBr9k30MhIecMttGny9JEiE5TMnKY2AgIYMpIdky/f4BbGxMW6dkaki2xP7IPJZkgV2WbJm2iYmOgY4NBOwgIGFhIvtkotEofX19WLZFwc6R1/IUcnn0jEkoFKJUKnH8+PEasnPrTduBO3oeHh52LCcBNvQUpm3gPy8v02WNwLCPWf9s2UPCpZwQvq+KotTMTdM0zp07hyzL7Nmzp8ZoxU0AjnbYlaJwV9iJ38DL7nu76CaBe6myc8vYxA1NkPDFKCnuRbo7EO2mF8RCMgyjRmtbfRG0Q7rtFl4II/FCsUBgQgGfREHKkS9lGVHHGPKPNt1wkyWZkFJeOJZtkSaNiYFkK0SUPixMBvqGCUtRx1MBzkuv0ClbxpTj3jzlMlzpvK+BDz8BO0hG3yBbyGBoBpFoBHXQR1QeQJEUZ0OnWCw6xRO6rjslsG4ibrS4xCOwMAXav39/Td7WtM2KhS5LMiYXiK9eNwRN05y5JRKJCm/dcDjsyM0aPVY3imrrbdjZtk0+n3euqa1u2HXbFawe6lXZWZblmACJGxqU87puo/jNGplvRr2wm7DrSbeVdtQr6Ypxzp075+Qkm3UTbqeYwmukKzaOzp07x/j4OGPTI6xoy6iS/zzJWqzpCQbUYe/SMiSsko3mK2FaPhRFxif78ck+bOm8Hyk+fKjoaFjYSEiolAnOOu8KJly8dKvEenIdTSkSCATpHy6XNZu2gYWJgtJQbyrIrlAokEqlnJbt1UQsnjAkqdwTrlHePCxHyFkbjqOYaZtE5MablcK8RlVVdF1H0zSGhoYYHBx0yLg6beL+4/f7m5Zww4U8sYieNU1zHuGrlRPifV6JuNOR7mbJ373JOjAw4JQ6z87OVrixubsPu4m42fcI3qvRbNvuke7FQjPTGy/EKIy8oVzk0MqnATrbJ008QieTSRRFYWJigpGREfJm2c3rwgUq/rabRrpQ6QA2OjhGwcxhWDrFgoZeyqGoMpYm4VfKpOcP+gn6whTJo1D2PXCixvNy7kK+QKGUR7H95xUJlV0kmpXgioKI6ojJnQIQCxUgFAo5OtRGFVhhJcow46SNNWxgyDdKVKk18nFD9L7z+/0VuedAIFBjcu5OTcTjcQzDcMijUbQurqVUKsXw8DBzc3MVBFMdCVenKASR1Nuw24n5YTGWyBE3Mot3l4y7+6y5yVicqxcfh91q6wiXCOk2Qqv25+7S4XA4jKqqjI+Pe9oEajdfLMpoG31+JBLhwIEDxONxZzEE5KDLFlHBsA0iShRZUsoGhnWq19xkCxdKTlV8aJSwwuX8LaaEXjDQdA3NLpLPZjE0A9uCYL8fxefDp/hQlQBFrUA2m8OnKgz0DRD1DWBikLezmLYJ2KhSAKXNy0nsrAcCAQzDwDAMRkZG6Ovrc8g4Ho83zMX6fD76fYP0N/CScMO9ESd63zVDo1JnMa960bokSWQyGUKhUN10iDhnqFVOiPGbbdh18nF6uza+3N2H3ccLIhYtlDRNc6rsxJoVTnb1IG5SvUj3IqFR1KcoiiN1csOtCFBV1SkdPnbs2Jbbtjc6tlqRIKRPPp+vwlfXfawiKUwH95LUVtEsjX7fECP+MeecxXm7q+PcRFwZyUgokg8JCySQJYVAXwBD8jsZXNM00DWDQqZArlSgkC9gWiaBqEooGiKoBlGt8qaVT1KJ0o8pmUjIKHjrpOCG+3uoJqpqiZM7F5tMJj1riS2r3J2j3kZcu2iU38xms47MzOfzkcvlOH36dE3apFmqyv23e2zxm2azWbLZLMPDww4pbaWwo5MVae0SeCMZm8gTJ5NJ8vk8GxsbTkrIHRWrquqskU46m20XLgnSbYR6xCgeL23brmmt3m702iyKrj5WjOtuqz45OVnTIqh6Dn7Zz1Rwru64IlcsSZITETVagOXuCmVbxPKbbSynzLa8SSYpEv6QSsAXJB6LAzA2OubkWXPZAsliCtM0a6VY/vYiDnfX5epqtXrnKRbehSo2u2kVWzAYdDbjwuFww8hzK6hOJQwPDzueyO60STab3VTBibh+RWdoUYjTqMJOEKkXIvbyCN/O97BVAnf/xhsbGwwNDREOhyvSE5lMhkQiweHDh3nkkUfYs2cPr371q7n66qt5/vnn///2vjy+qTJf/0mTNkv3faErFQIigsOi6FyqyFLByiiLCIKKsngFREdkEZiBcUTHhQER7xWXOzDoiAoOIgOD+hPmCshyAYelsSwttOmattnTbO/vj/Ie35yeJCdpUkrp8/n0AyQhec/pyfd83+f7fJ8vvvnmGwCt3WkvvvhipzQwB7p40GV5V/olp9tLoS6pQHW9gb728uXLsFgsSE9PF2xdBgJzGqO0BeuN6jXblLQOs6G8KzfahpBWyRjccIPAYXfAYrBAFinzsKMUcsNi+U7akulPJkaVISaTCampqV7Pgz+wrbBUS0xVAkajEY2NjXC5WtUNZrMZWq1WdFFMDGiGrlAo2gR0b8oJfzcJtuEEAJqamtDQ0ICEhARkZWV5BDahxg5vrc5A24LdtZB4iQVVL3iTsU2dOhWJiYk4e/YsTpw4gS1btiA1NRVff/01JBIJnnrqKezatQtvvPFGpzMwB7pI0PV28VBO98qVKzCbzUhNTUVubq7PTqVQy8CcTieamppgNpuRlpYmKD/jr8FfBk2/WAqFAhcuXBAnxSIS4KpagYBcDb2t3rRu4oTT5YStxQY4gMSEBEhlkZAS4exVSJ3gTyYml8tht9uh1+uRkJAgyl84UNDMk+/FIFQUE3uT4INyw3a7ndupiIGvmwS/4YTlK5OSkvwOTPXVYSdUsKM3AKVSyV3D7Qma4fBx8HVtJCYm4r777sOwYcNw66234ueff+Y8Q4BW7+ry8vJOaWAOdJGgKwTazmm327lMQYyJeKimR9AA0NDQgOjoaCgUCr+Wb/7el18ky87O5pzG+MUdfkCJkkdBIpVwGS6uMrE2qxXNJj0i5TKoFErIoxXMa8TDVyCmc+FoFm+xWFBXVydKrysG1N6zvr4esbGx6Nmzpwd/6sv/V6yWmE8ltIcbpmAzudjYWLhcLtTV1cFoNCIhIYHTbOv1+oB1zt4CMfXFoEY4Qo0dgVpihjrTFfN+rKKld+/e3OPl5eXYvXs3pk+f3ikNzIEuEnTZuyw1hGlsbERcXBwiIiJEBTsgNDIw1t+Xuo8RQnDlyhXRx8J/X19FMolEIljc8RaIlapWtYBMKoNer4fVakVaeiqi41Wggx0BQELan7k4nU4umGVnZ3MSMH96XX/eCSyok5lEIhHsJvOGQLTEMpmMkznR7DaUQYYt7NLRUvwEwZ9ygg3EQskFVcrodLo2Uja2YEfdyuhnAv4Ldtci6Aplw2VlZZgzZw4WL14MmUyGS5cueTzvjbrz9bg3+LvZ+UKXCLqA55ie2NhYFBYWIjIyEk1NTaK3P+1VJFBDHKlUyikigNYtaSDBnL0A6JfAV5FM6D28BWKLxYKmxiZODyuXy2ExW1tbfpVyRMpkiJC0DoEMFr4sF8XqdYUCCvXmBX6Z7kxpG1+z58SCvzba4GCz2ZCQkABCCHQ6HbRabUC+Dr5Am2HcbjdycnK8NoJ4U06w581gMMBms0Emk3msC2g1146IiEBeXl4bC1LWP4J9b7EFu1BK2YRkkELgf+bx48exYMECLFu2DOPGjcORI0c8jMo7i4E50EWCrtlsRnl5OVfUYLOdQPSNgU6PoAGaGuI4nU5OA+pLkeDvfdkLndXbcpkJ3CBwQ4KIX9QIfiCRSGC329HU1ASVSoXsnGw4I+xocdjhanHBYjKjsaHRI9jRwZNis06aTTU0NCAuLq7NNt/XMfMlRPyAwprY0GOJjY1Ffn5+WFQJjY2NaGxsRFJSUhsePhBfB2/Hz0rZvHkB+4Mv6RXNiKurqz2mdRgMBtHKCcB/wc7lcnFGRw6HI6AOOyHQLFdM0KW/9+rqajzzzDNYu3Ythg0bBgAYMGAAZ2CenZ2NXbt2YcKECR4G5oMGDRI0MC8pKRE0MJ87d66ggfngwYNFG5gDXcBPFwDX7cJuFSlKS0vRs2dPUQ0Pzc3NMBqNHPnuCy6XC6WlpYiLi+OyLW9fHLfbjXPnzqFfv35+39dkMqG6uhqZmZmcmxP7ng7Y4QDVHksQBQVk8B10qFdwREQE0tPToVAoYCTNsJMW4OpcBpUkBqqIGC7YWa1WLqiICcT0M2hHndhtfiAwGo2cMY1CoeDUAKHKOoFf7DsVCgXS09NFB3S+lpj+CMnErFYrN8svLS0tLFpTeq6io6ORmprqwf3THwBtOuwCUXVQSiQ6OhrJycncNp2/U/PWYScEu92OyspKv77WlZWVUKlUyMvLw8svv4wvvvjCw393ypQpyM/P5yRjRUVFWLp0KSQSCUpLSz0MzNesWYOoqChUVVVhyZIl0Ol0nIF5fHw8mpubsWTJEly5coUzMKctzytXrsTp06cRFRWFl19+mf2Oez2JXSLo0gKBEMrKypCTkyMqCBiNRuh0OuTn5/t8ndPpRH19PXQ6HVJTU5GSkuLzS04IwZkzZ9CvXz+vFzTNHOx2O+rq6mCz2bgKOxfoFFFwyR1XlbWUfyVQIlawBbelpQV1dXUedogSiQQOYofe3eRhdO6GG8kRaV5vGt4CcVRUFOx2O5xOJzIyMtpk+aEAv5uMrebzs05q1s1mnZQj9pV1s58RiCrBF/gyMavVCqvVCkIIFAoFV2ClMrFQnDeHw+FxHEKJCPta/rkTo+pgP0PIxJ91YmO5YhbeeGKbzYaamhq/38HLly8jPj4e2dnZYk9NR6Nrm5iHyvRGjCKB8sZUpJ+amur37k0vLCGag18ki4yM5C4kWmG3Wq2t2tNmO6KTWq0WZVIZpDIppLIIuCVujwm/LKeanJzcptLOFcvanLdWJa/QeeFvY2kV3Gg0cgFNq9UGXRATgphuskDcxIS2/xERER5UQihUCeza6OgjGuCSkpIQHx/fboMdPlhqJzExsY2uVwjerBy9qTromB/KaXr7jECc2Ohn0vNFqRB/EDuGqzPi+lx1AAimiYEP2tlExfB0HpperxdduRUKuv6KZPwKO4EbFmKEy+mCy+WGw+mAzeZEVXUt90V1uVwwGo2C0ikKGSIRgVbv3AhI4IYbURI5JBJxvC1ruUgLloAnD2u1WgULYmICMdseHEw3mbcONn4rMc06pVIp4uLiOAlVKCvxtANRJpMFbLAjVktss9lQXV0NiUQiWCgLBN5UHSaTCXV1dXC7Wz1sm5qaYDKZAqJ1/PHEtOYgk8n8tjqHsnjX0egSQddfptuehgfK8VGbQfZipEHa2x2XgIDADUgI4hJjuff2VSTzBQkiIJeoYI+0QRZJWv8NJZKUrRNhm5qauPczGo2cKxZ/CxshiUB8RCJMxAg3cUEhkUMl8W0AA3jKs4QsF9mMODExEUDggZjOFHO5XMjKyvK5PQ4EbCBWqVQc/0x3KmyXGJs9iyk6CYF23pnNZsHiKh/BaInlcjmsVitMJpPXLsv2ghDC7QTYgl8oionAL2odg8GA+vp6JCYmIikpCQC8ZsT0se6g20kRLL1AuSW73c6N6OFf0D4bGUBAJG5uK69UyEEi3HC5nHC7RbTteoEMkVfdvFqpgBZbq/es0+nkghTbhWW1WrksnXKJ9EeljBEVTNhBk4HKs/wFYlYiRs9nTEwMUlNTQ16MY1UJ/C04v0uM8tfe2nWVSqXguaM7gbq6Ok7BEWxw8NZwQhsm2IaTxsZGWCwWQXldsKDqB36WDoijdRobG7mbGD9jZ1Uo1dXVcLvdbXTWQk5s9KZMqbjrEV2ikAa0FkKEjoVWu8Xo52jBKyEhgfMGSExM9HrxXrx4Eenp6YLZWGvQdQGQAFe/FHKFHHBHQCFv/xeCFvOMRqNoyRFb1KEBGYBHIGGzOrYLKzExEcnJySHdegO/NJNQe02lUgmHwwGr1epXqxsIWB/d9PT0gGa48dt16Q//JiaRSDgNaGZmZlgUHE6nE7W1tbBarVzBj38To8XEYFUdbrcb9fX10Ov1XhMOsfB27mim6nQ6ERsbi+TkZJ9t2PTGUl9fD5VKhfz8/LCc3xCia6sXAO9Bl3JjGRkZPv8/LT41NDQgJSUFqampfi/Q8vJyzv+VDwICt8SJq8N50dLSAqfLiYZaHWxWG3fnZyVYYi5sNluLj4/3q5zwBf4XgmZ3QOt21263c9IpMVOPAwXVN0skEsHP8BZMAgnEtNJus9lE+egGAnoTs1qtMBgM3ARh+jsNpiDmDWyrc0JCAlJSUvzy4vxzJ9Q4wd/+m81mVFdXQ6lUIj09PSzFqpaWFmi1WrjdbkRHR3PXIEuHUQtHg8GApKQk1NTUoKWlBVlZWUhLE1bZdDJ0/aDrcDgEt/qNjY2wWq3o0aOH4P9zu92ckXhsbCyMRiNuuukmUVsXKluhxRoWhLQOgCSS1rMvkQBwSwAS0abd1GazweFwtMk42S8rLS5RzwKxZuuBgrWeVKlUHK/I5znp9joYsHxnoHSF2EAsl8vR1NTEUQnhytIp5x8dHc3tpviBTsgKM5BATKkuAMjIyAg6w/OlJaZG8g6HAxkZGYLXdHtBs1WdTie4O2NbnW02G7755husXbuWa6e/7bbbMHnyZA+vhU6MGzfo6vV66PV6D+E08Eu/e01NDeRyOXcx//zzz6IrwFSgTYl/+r6/FMkIJBGS1oALydWzKfy7YIsmNBDTL6tMJoPVauUywlBoSPlgLRfT0tI8ijJ8vSldIxX+s5mdr0DMfunam6Wz4Adis9nMdUepVCoPPWyoAi/fbcxXwY96wrI6ZzHKBFYy1x4bTF9wu91cBh0ZGQmpVMq1iIvhsMWCZrcRERFc448v2Gw2aLVaVFRUQK/XQ6vV4ty5cyguLsakSZOCWkMHo+sHXafTKVgwo8bHBQUF3GNmsxk1NTUghLQRwl+4cEFQ8C0EqktNSUkJWpHgC7RoQLuuXC4X3G63R5Br75eBZvqBBkIh4T/Nmvjba5lMxnGqkZGRSE9Pb5esyRtYKoF2egnxnPz1BRKIqf8C1fXSTqxAwd5k6Q9VJiiVSkgkEq5lNyMjIyxFI4fDwRWL2WteLIfNFsS8gT1fYm4c9PXUnS8/Pz8s10oH4MYNuhaLBdXV1SgsLPQIYt4kNpcuXUJqaqqobJLKp5KTk0MabNkMh781Zivr/GIYG0z8fUnp1ri2thZyuTzg4pK396RFMP6XFWg1Qo+Pj4dSqQyp3If9YvuiEoRaYQMJxPRmHUwxTgxcLhcsFgvq6+tht9s55U0glo5iwPLDgVAvQoHYF3VCs1WZTIbMzEy/1yTVG9vtdvTo0QOpqanXA3frDTdu0G1paUF5eTliYmJgMBiQmprKjVURQkVFBRISEvxyWoQQ1NfXw2QyITExEUqlst3ZCNt4oFKpRPXls1kJG+woByu09acjzh0OR9joCqp8oAU/hULhQQFQPSe7vmACMQ2EkZGRyMjICDgQ0oITe+7Yyj/9vRoMBm7qRzhanVmpWXx8PKcfZvl/+tMeU6KWlhZUV1cDaFVYtDeL9Jax0xtGXFwcEhMTOXWHt2PvItkti64fdF0uV5uJu9QUmhL3YhQJlZWViI6O5jSlQqCdZHQSgrdAF0hGxzelaY9agN36s8GEmuc4nU7uix3q6jS/4CdkGsN3wqKBTiqVtsk4vZ0/virB33SFQI+BBmLqOQygTaALFUfM2juKkZrxG074gVgoY2d3A8G6momB1WpFVVUVNwGYXod8Y32pVIqmpibOLLyLZLcsbqygy2r6oqOjodfrccstt4h6H61WC7lcjuTk5DbP+eJtvQU6NpDQP9kvKmu0wprShBL0fDQ0NHDbP/qlZbWcQusLBDR4uFwur/plX2u02+1tqAn++uRyOZqbm6HT6cKmSgA8W2szMjK44Zz8G4XQ+sTeaFkddHsDoS+tLuW2IyMjkZWVFZYsktX2Chkf8de3d+9erFu3DgqFAoWFhRg4cCAmT56MPn36hHxt1whdP+jS3m1qaUe3mwqFAmfPnkXfvn1FfTkpT8s2UwRbJOMHEqvVysmbqETHZrNxBZlwBA9flove1sdynGK8Eui0Dr1eH9Isiq81NZvNsNvtkEgkXKdWqFUJ7LHwVRz+1seeP3+BmNIilE8PR6HM5XKhuroaJpOJm4fWnqYJb7BYLNBqtaK1vTabDVVVVdBqtdDr9aiqqsKZM2cwZsyY60WZIAZdP+harVaUl5fD7Xa3EcGfO3dOtPaWbaYIhyKBZgRNTU3ceth++kCbJbzBlx2iL3jjOIW21gA4HjI2NjYsdAXwSxuy1WrleG52jYE2THg7bmqyQzW3wRyLv0AcFRXFrTszMzOkzRosqH6Y1gbosYhpmqC/Y3+BmDYUGY1GAo99AQAAIABJREFULrv1BUIIGhoaoNPpEBMT025znk6Orh90HQ4HdDqdoCQlEO0tbabIzMzkDDdCEWypWqCurg6RkZFIS0vjApevZgk24xTjuepyuaDT6Tg7RF9FQ7Hw5qcLtHorJCQkcC5doaRGWF2vry4sb6oEse5mdCwP9QQWIxcM9DhstlaPCb1ezxXIQp1xAsJtwmLWJ9Q04cu8hg3q6enpftdNfRzovLyUlJSuwt16Q9cPuvTCEUIg2luqWU1JSWlX1xULm82Guro6OBwOpKWlico6WS9d+if1XGUDMdXo8i0XU1NTw7JlZZsoEhISIJVKParW/Gwp2BbY9qoS+Bwi6+XA7iZMJhOam5uRnJyMpKSksAQCauricrmQmZkJpVLpNeMMNhDTZp/a2loP9UOw8NW9BrSe36SkJCQmJvr8jlD5o06nQ1xcHPLy8sLSSdkJcWMH3UuXLiElJcXn9of19KTuSG63G0mpiYiKimr1zSXSgLatwZjS+Hs/IY1uVFQU14EVLgkYa5LtrYnCV1cdG4x9ZewslRBqVQKbsZtMJlgsFhBCPKZz0J9QcdJUMSAmqAcbiB0OBzcLjQb1cIDt4JTL5VxQ5reIy2Qyzmearis7OzvoRpLrFF0/6ALg2hf58OeR4JW3lREQ4obT5QIIYNQbUVdT75Et0W0rv1IbKlMaX6C8rcVigUql4mgK/qia9m5b2awz0G4yOriQDcZCXXVUQuSPSmgv2O03VVgI6WDby7HTphw6tj3YXYevQEwnOVgsFiQmJoZNbsWes8zMTA9VilCL+AcffICvvvoKmZmZ6NWrF4YMGYKJEyf6lGEGixkzZkCn03HZ9urVqzFgwADu+YMHD3Jz0u677z4899xzIV+DF9wYQdeb01hVVRWUSqUPjwSBIpkEkFDbWuYxV4snv2m1Wj221QC4ETbBbIvFwJflopAGls2WAtGY8ttqQyVn4zdzWCwWzuovNjYWMTExorrqAgGbqfsL6vyGBPo75mfEQoGYasOpsXi4JIC0m5BOcrDb7ZDJZKJ1zmJBs1uxlAUtaGs0GjQ1NaGiogKlpaWYP38+Ro0a1a618EEIwX/8x3/g+++/F6Q4bDYbiouLsWXLFmRmZmLOnDmYMWMGioqKQroOL+jaM9L8gTUyJ4R4zGnyWSTjx28iPC/M5XJBr9dDp9PB7XZDIpFwtoVsoAtFx5rBYOC8Z4XG2HgbVcNqTOk4czZjZ7fV/KAuZt5WIKBTEuRyOWfEnZGRwfHDQhMcWK/fQEF/FxEREaIKqtQoh60BUAcsq9XqMcWBPXdOpxONjY3tNi/3BfZ3w3oZ8OV/RqORUyUEE4idTidnp5idne23HsLnbidOnBh27vbixYuQSCSYNWsWdDodJk+ejEcffZR7/qeffkJeXh433bukpAR79uzpqKDrFV0q6NKLjw86Vod2ktFg6zOQ0LeRgJvXSAQGULBTFVJTUzldp9D0AbZjLdBtv9Vq5TKbHj16BFRhZ4NXQkICAE9+02q1orGxEQ6HAzKZDC6XC1FRUdznhKtZg1IJN910k+AEB3bbqtPpAqZO2AGd/jS3/iCVSgUDMdUP0/lhQGuGVV9f3+5iIh8sZcG/4bI3WwqhQMyO1BFqwWYLcr6GT7KwWq3QarVwuVzIz88XbCwKBwwGA4YNG4bf//73sNlsmDFjBgoKCnDXXXcBAOrq6pCamsq9Pi0tDbW1tR2yNl/oUkHXGyIiImCxWGC1WrkijijNqhMAvd4IPDJfNuNISEhAYWGhx8Upk8kQGxvLFe/4HWv19fVoaWnh9JHetv2+LBfbe07YjJ12k9ntdsTFxcHtdnMVd36Qa8+4cNqsIZPJfGadEomEG/HOBmK2ok7PIb/rLyoqiguEMTExKCwsDEvWSWerUXkeNT6i6+MPmGR/x4EEYlYPGwhl4SsQ0+uQDcS0OEYIQVZWlt+CLG0kobWL3NzcDlUm3HbbbbjtttsAACqVChMnTsT+/fu5oCuUgHWGQl6XDrqURlAoFDAajaioqAg82+RZ9PJNacROqvUWRLxt+xUKBdxuN8xmM+Lj48MWOPx1k7HOUkKz1sRSJ+yOIFiu0xt1wmZz9BxKJBKoVCqufTeUXWuA9/lh3uaasUGOBmIxqg7aYRkdHR0SykLoHNIEQqfTcTx1VVWVz10FzbpdLhcKCgo86iUdhWPHjsHhcGDYsGEAWq8Fln5KT0/nxicBrZmvmLFd4UaXCrqsDwJbJFMoFMjNzRXMNmmRie+PIBQQWFMaoWm4wayXv+13uVxcFT8iIgJSqRTNzc2w2WwBN0r4Al/X63Vcu8CUWvYcClEnrCKBX8Di7wjaCxpEIiMj4XA44HQ6kZaWBpVK5XGzEOqqC8YikaUsxM4PEwrE/JHrlJ5gf78mkwk2my2kU5H5YAdD5jNzx7ztKlasWMG99uabb8aIESPCHnBfe+01NDU14dVXX/V4fN++ffjrX/+Knj17cpTVO++8wz0/YMAAXLp0CRUVFcjOzsauXbswYcKEsK5VDLqUeoF+6QLpJOO3vVIRPd0O0uDR2NgIu90eNlMawLOJgtXbCjVK8LPNQBo5KD9MTdzbe/Pw5WpGq+vJycmIi4sLiwyMdkcpFMKuZoB3Zy6x0jC2TTgmJgZpaWkh33nQOkBzczNMJhN3rviFsPbecAFPNYfYxhCz2YwDBw7g5MmTqKmpQVlZGerr6/H99997cKehxKFDh/Dcc8/h7rvvbhN0//CHP6CmpgYXL16E2+3G1KlT8dhjj2H8+PF47733kJ6ejkOHDnGSsaKiIixdurSjKIauLxkjhECj0QBozWxVKlXQ1W7Ky5nNZhgMBs5khQa3QIOcPzidTjQ0NMBgMAQ82ZcNxOzUBiHqJFz8sNDx1NbWwmw2c5x2oK25YsBK2sS2vLLwN6uOrlEikXD2g2I7G4MB245Mmxz4DTE2W9sJDoFODwnUU5flbhMSEpCbm8vd2GiXXzjQ3NyM2bNnY+zYsSgtLW0TdCdPnoy4uDjU1dWhd+/eWLFiRVhmuwWJrh90gVbfBL1eD4vFAputdaotdfRig6WY7JdmAdTIBYBHgGODXLBG3OznxMXFISUlJehAzp/aQP+k+lxCCMcPi/EVDnYNvrSwrEdCMNmm0OeE2t6R31VnsVjgcrkQGRmJmJgY7vcdimyTglVziMk6hebVAW2nh/ADMfs5Ym/uLHebm5vbodztggUL8Mgjj6C6uhpHjhxpE3SfeeYZzJ49G7feeiveeustaLVavPnmmx22Pj+4MYIuC1qEMpvNXMsnHZHNfslptZvKzdjqOt8KkQUb5NhMhOUNhbrVKKi43d/ntAd0LEtDQwMIIZBKpWFxNAN+mSIslUo5/1kxCNTshxawAv2cQMFqe1NTU9us05cPRiCw2Vp9e8UObBSCt+khADx2PM3NzZBKpaI+h3LXVJ3DZrcdgc8++wznz5/H0qVLsX37dsGgy0Kv12PkyJE4evRoh63RD268oCsEh8MBk8nEBWOr1QqXywWJRIJ///vf2Lx5M0aPHo3p06cHtfX2lsnxxf06nQ52uz3k3gL8YxXqJhMKck6nM2hZGDtOPVQdWN7MfqjeOiEhAUlJSSHNNtnPFuOnyw9ybLYpRtXBzsELB9VDAzEtdlosFkgkEkFFAn93ZTabUV1dDUIIcnNzw9K+6w9PPPEE6uvrIZVKud3rb37zGyxbtgxAq6rjiy++wOOPPw6glYq47777cOjQoQ5fqxd0B10h0HbKefPm4ciRIxgzZgwefPBBxMTEtDGiViqVQW1haQCxWCzQ6/Vctq1SqdpkSaEA6/sgduvN+iPQPylv6G2NYgxwQgGqsqitrfWQgNEgx+ew23MeWXlWoH66/mbVsWukmmjaKh4OD2LglzHmdDCkTCYTpCYiIiJQVVWFffv2IS8vD1lZWbj11ltRWFgY1uzWmypBq9Vi0aJF0Ol0KCgowPDhw3Hq1CmP17lcLhQVFeGdd97BgAEDsGHDBtTV1WH16tVhW2+AuLHbgL2BFseGDBmClStXorCwEG63m3OhMplMnKwKQBtaQsy2PCIiAg6HA83NzdyXmWbENAvRarUeXULBjM1h+/EVCoWHdtQfpFKpoCyM7ahj1yiVSmE2m/02OLQX7Oyw3NxcD5UFm8kF27HGHis1fA9WniWRSLjROEINMXSNFosFADwCMM1AQwVfWbSQVtzhcECv16OxsRHHjh1DXV0dZDIZZs2ahYULF4ZsXSwOHTqEHTt24O67727z3KpVqzB16lSMGzcO77zzDr777juuy+2ll17CiBEjcO+99+LPf/4z142Wn5+PP/3pT2FZa6hxQ2e6YuF0Ojlu2Gw2c8WViIgIjyId7TSisFgs3PgfX8Mm+V1C7FgfX25mFB0x3ZcQAqvVirq6Oq5A53A4Ah7tIwZs0AjEEpOvLeUXE/ldf+EsyPFBW2vp0FP29x3oUE5foC25Yt3NWO42MTEROTk5MJvNOHPmDNLS0tCrV69gD9krfKkSHA4Hbr/9dhw5cgQymQzV1dV49NFH8e2334Z8HWFGd6bbHshkMg9rSPrlZgNxU1MT1xFz8eJFfPTRR7j99tvx+OOPC06zYOGtS4jvjeB0Oj2CfFRUFJqbm2EwGMJqws2nEnJycrjGB3aNzc3NHhpnti1X7LqoFlapVIru9qMIxOwnMjKSu3EKDVIMFdgsmvXMUCqVXrvqqFkNe0MTahFn4W8wpBBY7rawsJBr0ElISOBaacOBlStX4rnnnuNkayyampoQExPDUS50WnBXQnfQDQLsl5tKaKiv6YoVK/D111/j17/+Ne644w7U1NSgsbGxDXUghpYQcjOjwYNupylFQtUa7eU1+WBVCXwqgeUrabGFFuqoG1dDQwPX8uqr0u9wODjvB75na3vA7/pzu92oq6uDXq/nipgNDQ3cFOhgbxZ8UOVIfX29X+MYbx4JbNOOr646yt0qlUqvnYUsqP1kc3MzEhMTkZubGzZemY/PPvsMmZmZGDZsGLZv397m+c7qlxBKdAfdEIEGv6ysLHzyySf41a9+BafTCYvFwknWqJMX/ZLxaQkx7aQREREwmUwAgPz8fMhkMkFek68fDnTbzKoS0tLSRLW7AsK2iGyBSa/Xo6amBsAvvKbD4YDRaERSUhJ69OgRti0+7VxTKpUoLCz0CDS+bhaBqjrY1trc3Nyg5IDszYJdI5u10y5JAIiOjoZKpYLT6YRUKvW6RnoO+NltR2H37t2or6/H+PHjOVXCK6+8wqkSkpKSYDKZ4HK5IJVKUV9f3yn8EkKJbk63g8GnJagcil8A4qsF2NE/rI8qH/ytKp8fFtPuGm5VAi2CNTc3c7QMgHYXE70hmGGNgG9Vh5AsLNDxPO0BewOJj4/34Ij5XXVXrlxBWloa3G4354iWk5PTYdmtN3jT386ePRslJSUoKSnBu+++i7q6Ovzud7+7RqsMGt2Ssc4KqmRgi3RUDhUZGQmn04lPPvkEJpMJL7zwQlA9/3x+WEibq1QqufE/Uqk0bA0bgLC2F4DXmwW/CCY2kPG3+KEYASTkMUGVC3R6QzjnlLlcLq7FOjMzU/AGwnbVGQwGPPbYYzAajUhOTkb//v1x1113Ydq0aWGR+AHAunXrsHfvXkgkEkycOBFPPPGEx/MbNmzAF198AbfbDYvFgoULF+Ls2bOcKqGqqgpLliyBTqdDZmYm3nrrrc7U3isW3UH3egK9GPfs2YPXXnsNSqUSTz75JG655ZagZGtCYLM4i8XiMaQxNjbWw+wnVKCa27q6OlFZtK+2YX/UjM1m42iMjIyMsN1AaBA0GAzcnDohj99QZO1URyzWcIfujhoaGmA0GtHQ0ICzZ8+irq4O69evD4tnwpEjR7B27Vps2bIFTqcTY8eOxfvvv4+ePXtyr5k7dy7mzJnDeeGGAtTgqhOhO+hej9i0aRPcbjcef/xxREREcJ10fNkaP2MVW/FnM8G4uDgkJCR4ZJs2m83DZL09kjAaBAkhyMzMDDoI+po4TNdnsVi4aRH+lCPtAa3+K5VKpKenc9t1XxRPMGY/vgZDeoPJZEJ1dTUkEgny8vI6NFOkUsKqqipMnToVn376KTIyMrjnf/3rX+PWW2/FlStXMGTIECxevDhorTftVOyE6A66XQ20us2nJahsjc+N8rMi1lvAG5XAl1vxbS/FVPlZKZMvLro9oIU6g8EAg8EAAG3MiEKZtbNbfCrP8gdfFqK+fDACHQxJqRu9Xo/k5GRkZ2dfE+52/fr1+PDDD1FcXIw1a9Zwx2Q2m7Fw4UIsX74cPXr0wJIlS9CjR4+gpvSy2e3+/fuxd+9elJSUYMCAAWFzggsA3UH3RgCVrbGBmI6lp1/uqqoqfPzxx5gwYQL69+8vWpVAwfduoP4VQpIwqrkNpq02EPALZdHR0YLca3u3/NRTt6amBnFxce12a/Nl9kOlYC6X67rIboVgtVoxd+5cjB07Fg8//LDga86ePYtly5bhyy+/DOozXC4XXn75ZVy+fBl33XUXMjIyMHbs2PYsO1Tobo64ESCRSAQnFJjNZjQ3N2Pjxo3YuXMnbr31ViiVSjQ1NcFqtQZkV+hPEtbc3MwJ7oHWQZPh8u3lc8Q9e/bkgqi3+Wo0uBkMhoC6/lgdsZjpuGLg7VxS74zIyEgQQlBZWelT50xvOrRJ5lpltwBw4cIF2O129O3bF0qlEqNHj+Z8roFWX4WDBw9i4sSJANqO2PEHKiWjKCsrw8WLF/GXv/wFP/30EyoqKvDee++hZ8+eGDlyZGfkeruDblcH7aZraGhAWVkZNmzYgLvuugsWi4Xjh/V6PSdbC8ZAho70iY6Ohk6ng9VqRWJiIhQKBWw2W8BjkcSA78vgjyMWakDwNhGZLwmjut3ExMSw6ohpYHc4HMjLy+MUEN50zps3b4bNZkNeXh5uuukmFBUVISUlJSxrA/yrEs6dO4dnn30W1dXVGDduHFauXIlvv/3WY0SOQqHA66+/jttvvx3Z2dnYunUrRo0aJXoNUqkUVqsVBw4cwIgRI5CVlYUrV65gxIgRyM/PR2ZmJkwmE/71r39hyJAh1zzbF0KXoBdMJhOmTJmC//qv/0J2djYOHjzIjei47777OL7o3LlzWL58OUwmEwYPHoxVq1ZBJpO1cTV64403wjaTqjOC+iqwtARrAs8v1HmbH1dTU4OoqCikp6e3qYyLGYskpkmEncIciC+DWLCFOnouCCFQKpUeznChdN9iC5qJiYlISUnxa+Jus9nw+eef4+DBg6ioqOBGs3/22Wfo06dPyNZGIUaVcP/99+Pll1/GgQMHsHnzZiiVSkyePBnz58/HrFmzsGDBAvTv3x979+7F22+/DYfDgV/96ldYtWqVTyWF0+nkbv6HDh3Cq6++CpvNhn79+mH+/PlISEjgOOzY2Fjs2rULR48exapVq0J+HgJA1+V0T506heXLl+PSpUvYs2cPUlJSUFxcjC1btiAzMxNz5szBjBkzUFRUxF0UAwcOxLJly3DLLbdg6tSpmDNnDh544AHO1chisWDRokXX+tCuKWhbMRuI+d10CoUCly9fxqFDhzBixAiu8UBsEGS7wFglApsNs00iNLDL5XKvs9BCAbbJISUlBbGxsW2414CnSnsB270mVtVBeeWIiAjk5eUhLi4Ozc3NuHDhAvr37x+28Tm+VAlVVVV47LHH8M033wBondS7fv16bN68OejPY5UJZrMZZ8+exdGjRzFmzBhkZWXhhRdegFqtxtSpU3HhwgVs3rwZ6enp0Gg0ePbZZzF06ND2H3Tw6Lqc7rZt2/C73/0OL774IgDgp59+Ql5eHnJycgAAJSUl2LNnD2666SbYbDYMHDgQAPDQQw9h/fr1mDRpEo4ePcpNEX3ooYfw6KOP3vBBNyIiArGxsR6VedpNR7fbGzZswD/+8Q/ceeedKC4u9jDyFhMQvXGarKUkLQwBrV/CpKQkJCUlhU3Yz45WZw13vFk20qnSLS0tHqoRf+3XwQyGZLnblJQUZGdnc+chISEBgwYNCuGZaIvIyEgPVUJ6ejr3XF1dncdwylAY1dBzd+rUKSxYsADJycm4dOkSRowYAaVSiZKSEuzcuROHDx/GgAEDMGTIENhsNqxYsaLT8bgsrvug+8c//tHj3/xfflpaGmpra71eFDeCq1GoQItTiYmJ+Oqrr3DixAm89dZbGDx4MJcNNzY2ghAStAm8TCbjgj1rYE4LfWazGTqdTvRYJLGgRjhiRqtLJBLBQp2Qm5lQoY5mtwBE+xFT6ZhUKkWvXr24z+1oLFiwALNmzcLcuXOxbds2TpUQKqMaWviiE12WLl2KyMhIrFu3Dj179sSaNWuwefNmvPLKKyguLsapU6ewa9cu3HzzzdwUic6O6z7o8uHtly/2cZPJBKfTicrKSmRnZ2Pp0qU4fvw4V9SYN28eRo0aFTBv3NUwe/ZszJ49m8u06A2NdtNRWiJYE3gamOhARL6BObvdb2pqajMWSawaA/jFx0ClUoly6RIC382MngvKY7OGR4QQqFQqTrPsq8LudDpRU1MDo9HYJrvtSPhTJaSnp6OhoYH7dzBGNawygf4pl8uxc+dOPPfcc4iJicGDDz6I//7v/8ann36Khx9+GI8++igOHTrkwS13dnS5aMD/5dfV1SEtLc3rRcG6Gp0+fRpLlizxCMSnT5/GX//6V48LyGazYdmyZR688f79+1FUVIRFixZ58Mbbtm3D1KlTO+bgOxDevvgRERGCUyjYbrr6+nqvJvAmkwllZWWcqbjQtps6uimVSs5Ski2AGY1G1NXV+R05FKwRjliwDRotLS3QarVcUHY6nW3WSddIeW2q0JBKpejdu7eoJoxgQakiACgqKuLoOop3330Xe/bsQUFBASQSCRwOB+bNm8c936NHD8jlchw/fhyDBg3Cl19+ieHDhwe0BqlUCoPBgA8//BByuRxDhgzB6tWrcfjwYWzbtg1PP/00br75Ztx7773YvHkz7rrrLmRnZ3Pys+sFXS7oDhgwAJcuXUJFRQWys7Oxa9cuTJgwwetFERkZicGDB2P37t04fPgwBg0axNELFosFWq0WK1asgFarxahRozBv3ryAeeOuGHQDQWRkJBISErgMkGpm2SGhjY2N2L9/P7Zu3Yo+ffrgD3/4A+RyOSdl8wepVNpGo8zyrvyRQxKJBCaTqY2+N9Rgi3LeOvL463z++edRXl6OnJwc9OvXD3fccQfUanVY1gcABw8exP/+7/9ix44dkEgkeOqpp7Bv3z4PKZfJZMIDDzyAkydPQiqVYuzYsRg3bpyHKuGNN97A8uXLYTabcfPNN2PGjBkBrePQoUNYs2YNRowYwdUMxowZg40bN2L8+PEYPXo0CgsLceeddyIpKQnZ2dmhPhUdgi4XdOVyOV599VXMnz8fLS0tKCoqQnFxMQB4vSh+97vfebgaUb5Mp9PhjjvuwOrVq6FSqTBnzhx8/vnnUKlUAfHG3fAEq5mls6/Wrl2Ljz76CDNmzEBJSQksFguampoAoA1/K1bfKzSzjI5QojKk5uZmWCwWUQ0SgYIdDOlrCga7ToPBgJdeegnl5eVoaGjAzz//jE2bNqFXr14hNYhhkZqaiiVLlnCqh8LCQmi1Wo/XnD59GrfeeiukUimGDBmC2bNnA2j1B6Ho06cPPv/8c1GfKeSZcODAATz00EN4/PHH4XQ6cfz4cbz22msYO3YsJk2ahJkzZ2L//v3Iz89Hfn5+O4742qLLBN3vvvuO+/uwYcOwc+fONq/xdlH06NEDW7Zs4f49YsQIAEBOTg6nagCA6dOn48svv+SCOAshfnjLli2oqqrCuHHjuC1bt4ZYGBMnTsSkSZM8shfWBJ4W0JxOp+CEXX/6XlYtkJSUhOTkZG4kvbcGCTbIBzLuPZjx6nSsj9FoRE5ODu64444O427ZOWjl5eXYvXs3/va3v3GPmc1m9O3bF4sXL+b8EjZu3BiUXwLgyd3SqdUSiQSXLl3yuLH06NEDCoUC5eXl+P3vf89Nabne0SnteToLNBoN9u7dy/2btiyK4Y0PHjyIw4cPY+DAgfjyyy9x5swZ7Nq1C8uWLcPGjRuxe/dunD59Gvv37wcALFq0CCtWrMDevXtBCMG2bdsA/DIZdc+ePbjllluwcePGDjwDHYecnJw220WZTIa4uDhkZWWhV69eGDBgAPr374+CggLExsbCbrejpqYGFy9eRFlZGS5fvoz6+nquGEphsVhQXl4Og8GAvLw8j+YDyrsmJSUhKysLhYWF6NWrF+eroNfrUVFRgbKyMly5ckXw/VlYrVZcunQJLS0tKCgoEGXwo9frcenSJdjtdvTu3Ru5ubnXpFhWVlaGmTNnYvHixR6ZZHR0NDZt2oS8vDzIZDIu4wwWUqkUjY2NWLJkCV588UXMmjULpaWlyM3Nxd///nduF0KlgZRrX7BgQXsPsVOgO+j6ACEEr7zyCvR6PRwOBz799FOMGjXKgzd2uVzYtWsXhg8f7sEbp6amIicnB3fffTciIyNRWFiI8vJyjguWyWQcF1xVVdWGC96zZw8cDgcnBmcfv5FBJWs5OTno06cPBg4ciJtvvpk79yaTCVeuXEFZWRmOHz+OBQsWYMKECVCpVMjJyRElz6L8cEpKCnJyctCrVy8UFBQgPj6e42gvXLiA8+fPo6qqCo2NjVzjxpUrV5Camors7Gy/WmWHw4ErV65Aq9UiOTkZffv2DWuxzBeOHz+Oxx9/HL/97W/x4IMPejyn1Wo9doiB+iUArdktRW1tLZ5++mkUFBTgD3/4AwYMGICFCxdi8uTJqKysxKJFi7B27VpMnjwZgwYNQmFhYfsOrpOhy9AL4UCfPn0we/ZsPPLII3A6nRg9ejTuv/9+AAiIN6ZbtunTp3driEMMVsnAytZ++OEHPP/880hKSsKzzz6LxsZGNDVLyBHJAAAR/ElEQVQ1cbI1hUIBlUolevgk5V2FDHRYFYJcLofZbIbb7fY5Fonqj2UyGfr06XNNKaPq6mo888wzWLt2LYYNG9bm+fb4JVA5nFQqhU6n4zrpaI0EAObPn48TJ07gyy+/xObNm3Ho0CGcPn0af/zjHzFgwICQHmtnQHfQFQDLD0+bNg3Tpk1r8xqxvHFZWRnmzJmDxYsXQyaT4dKlSx6vF6sh3rBhA3bv3g2n04k//elPePHFF7s1xF5AKYP58+fjkUceQWRkJCdbo/wwK1sT4m/9QSKRQCaTcTK1Hj16IDo6muOHWQ6aBvkjR44gKSkJKSkpcLvdSEtLQ1ZWVlipBH9SsHPnzuHJJ59Ec3Mznn32WWRkZEAikWDKlCn47rvvOGXC6tWr8fTTT3N+CXyzGz4qKytBCOEUPt988w02btyIsWPHYtCgQZBIJDh//jxuuukmAMD48ePx3XffISYmBsXFxYJ1ky4DQoivn260A8eOHSN33nkn2bVrFyGEkB9//JE89thj3PM7duwgS5YsIZWVlWTkyJHc40ePHiXTp08ndrud3HbbbeTAgQPk4YcfJhUVFeSee+4hM2bMIP/85z/J/fffT2praz0+02q1kqKiInL58mXicDjIzJkzyffff08IIWTcuHHkxIkThBBCli5dSrZu3RrmM9B54Xa7idVqJfX19aS8vJycOXOGHD9+nBw7doycPHmSlJaWkoqKClJXV0eMRiMxm80eP7W1teTUqVOkrKyMGAyGNs/TH4PBQGpra8mFCxfIAw88QNRqNenTpw8ZO3YsWblyJTEajWE7xh9++IE8/PDDpKWlhdjtdu66YRGua+Kll14iY8aMIU6nk5w7d47cfffd5M033ySEEPLzzz+TJUuWkLfffptYrVbicrnIU089RT766KOQfHYngde42s3phgl0y/bGG29g3LhxACCKCwbQRkNcWlqKJUuW4Ouvv0ZRUREn6aEa4pKSEqxfvx5ut9tDQyyGN75RQRUQKSkpyMvLw80334zbbrsNffr0QUZGBiIjI2EwGHD58mVoNBpcvHgRWq0WJ0+exMKFC3HixAlkZGT4zVSlUinkcjkcDgdWrlyJnTt34qOPPsKDDz4It9vttSAXCrBSMFpXYKVg4bgmHA4HAODll1+G1WrF3/72NxQWFqK4uBh79uwBIQS9evXCvffei7Nnz2Lu3LkoKSm5rtp424uut7fsJPjggw/Q0tLiMV56ypQpQWuId+zYgczMTCxcuBCzZs3Cxx9/jCNHjnRriEMIXybwRqMRH3/8MTZv3ozevXtDpVKhoaEBZrPZQ7bGgjDeEVFRUR7c7R133BH24/EnBQvHNREZGYnq6mps374deXl5ePPNN3H77bdj5syZ0Gg0eOONN7Bo0SKMGDECd955Jy5dugSlUnldtfG2G77S4GuQknfDB37++Wdyzz33kO3bt7d57p///Cf5z//8T7Jz507y29/+lnv8hx9+IDNnziTHjx8nU6ZM4R5ftWoV6devHxk7diz58MMPudfef//9ZNSoUeStt97iXnv27Fny0EMPkdGjR5Nly5YRh8NBCCGkqqqKTJ06lYwZM4bMnTuXmEymcB36NUdjYyMZOXIk2bZtG7FarUSn05GKigpy7tw58n//93/k2LFj5MSJE6S0tJSUl5cTrVZLzp07R44dO0YqKyuJy+W6Zmv3dt3wr4ny8nIyZsyYdn1WfX09eeCBB8jGjRvJ5cuXydy5c8mMGTOI3W4n//rXv8gDDzxADh482K7PuE7QTS9c7+BLetqjIT5y5AiOHj2K2267DV988QW2bNmC0tLSbg2xDyQmJmLfvn2YNGkSFAoFkpKSkJuby8nW+vbti6ysLERFRcFkMkGr1cJut6NPnz5hnTbhD76kYO01qWFlYBSVlZVISUnB008/jZycHLz77ruoqqrCJ598gmHDhmHo0KGCBegbCr4i8jW4O3RDAFqtltx+++0eGcK5c+fI8OHDSXNzM7Hb7WTmzJnkq6++IjabjQwfPpyUl5cTp9NJnnzySbJ7925CSGvR5NixY4SQ1qLJpk2bSGVlJRk+fDj58ccfyYwZM7j3Z4t89957L/c4v8hHs16tVktGjBjREafjuoDT6bzWSxC8bvhgr4mXXnqJbNq0SdR7u91u7u9ff/01+eqrr8j58+eJTqcjQ4cOJRqNhnt+/fr1RK1Wk/Pnz4e1cNjJ4DWudnO61wG88cPt1RAbjUaMGzcOxcXF3T7EIUZHdJTxx1Sx2LBhAz788ENYrVbMmTMHCQkJSExMbCMFC9akRiKRoLGxEcuWLeP46o0bN2LevHmYMmUKVqxYgQ8++AB2ux0WiwX33HMPlEplyJ3crkd0B93rAMuXL8fy5csFn2uPhhgA5s6di7lz56K8vLzN6wPxIaaPd6NjQMdUCf3egFaDmg8++EDQJOeRRx7h/h6ISY3dbvcoFm7fvh233347nnjiCSxbtgyZmZno1asXhg0bBo1Gg+effx7nz5/HtGnTsHjx4sAOsAujm9O9AXHhwgWcO3cOADhD6h9//DFoH2IAeO211+B2uzFu3Dh89NFHAIClS5di9OjRGD9+PMaPH499+/YBaPWlKCkpwejRo7F27Vruvc+dO4cJEyZgzJgxeOmll8Iqp7reQcdUeeNgT58+jU2bNqGkpASrV69GS0tL0J/1z3/+E0BrC3ZtbS2OHTuGmpoaKJVKnDlzBpMnT0Z0dDTeffddHD58GAcOHMDGjRvx6quv4i9/+QuefPLJoD+7S8IX93ANeJAbFkajkXz99dfk2LFjpKWlhRDiyZuFEt9//z156KGHSEtLC2lpaSFPPPEE2bVrlygumOX9Zs2aRXbu3El+/PFHcvfdd5OVK1cSq9VK7rnnHnLhwoXu5o0OwD333EOuXLni8ZjJZCJPPfUUKS8vJw6Hg/z2t7/1UKMEgoqKCjJixAjyxRdfkAMHDpDi4mIyf/58Mn78ePLAAw+QqVOnkgMHDnCvf/jhh8nJkyfbdUxdBN2cbmeGzWbD+++/j7KyMkRFRaGyshJz5szByJEjcezYMcTFxaF3794h+7yioiKcOnUKv/nNbyCVSjF69GiMGzcOSUlJQfsQ5+fn4/nnn4dOp4PL5YJcLu82gL9GoK5gFDNnzsSyZcuCsmLMzs7GvHnz8P777yM3NxcffPABsrKy8Pe//x2LFy9Gv379cPjwYRgMBuzbtw/x8fHc77YbwugOup0AMpkMp06dQu/evbF06VL8/e9/x7///W+Ulpbi8OHDMJvNUKvV6NGjB4YOHYoBAwbAbrcjLi7O53wtX1iwYEEbq7z2+hCzk2JdLle3Afw1glarxcGDB7kxNiQIVzCKiIgIjBo1CocOHcLJkyeRlZUFl8vF0UUWiwUZGRn49ttv0bdvX87Ephve0c3pdgLIZDIsXLgQly9fxosvvog+ffogJSUFJ06cwOLFi7Fjxw4UFBRw3UQHDhzAsmXLUFpaColEgvLycly4cEGwuNWRWLBgAQ4dOoTq6mocOnQI77zzDpKTk6FUKjF9+nTs378/4MLca6+9hiVLlgDwzvlqtVpMmzYNxcXFePrpp2E2mwG0TtCdPXs27rvvPkybNo0bkNnVQV3Brly5AkJIQK5gQoiJicGsWbOQkJCAPXv2cMqMgoICTJw4EdOnT8crr7zSHXBFojvodgJs374djY2NWLduHQYOHIinn34an3/+OYYOHcq1Rw4YMADZ2dlQq9WoqKhAZmYm56T/1Vdf4e2330ZdXR1MJhO2bt2KTz75BGfOnOmQ9QsV5nbv3h108wbQWrCTy+XYsWMH91igTRp//vOfMXjwYPzjH//ApEmT8Mc//jGs5yFUMJlMuP/++1FZWdnmOf6Nh71ZzZo1C//+97+RlJTEuYIVFxeDEOLXFcwfCgsLMWXKFKxbtw6HDx/G7t27sW/fPq6Qp1Ao2vX+NxK6g24nQFpaGt5++22cPHmSG0JoNBpRWlrK9eq3tLRwk2TLy8uRmprKBV29Xo+CggKkp6dj2bJl0Ol00Gq1WLVqFV544QVu5M1PP/0Uli17ZWUlli9fDrvdDrvdjm+//RZDhgwJ2gAeaK3O6/V6zJ07F4B3cxZfRu/ff/89SkpKAAD3338/Dhw4wBmydFacOnUKjzzyiFcpGP/GM2vWLE6ju2nTJvTv3x8AMGbMGOzatQt79+7FmjVr2vhCBIqIiAgUFxejoKAAzz77LI4dO4Z33nkHgwcPbtf73ojo5nQ7AQYNGoRHHnkEmzdvRlNTE4qKijBlyhR88sknOHHiBKRSKTZt2oQ+ffqgpaUFzc3NGDRoEGQyGQwGAwwGA+euv3TpUlgsFiQmJuLRRx/FyJEjsWjRIjQ0NGDWrFkoKChAU1MTNm/ejMTERJw+fRo9e/bkJvUGA6HC3Lx585CYmBh084bVasXq1au57DeYJg32/8hkMsTExKCxsRHp6elBH2u4QaVgfN9bQPjG05HFRpVKhfnz56OqqgojR47skM/siugOup0ASqUSkyZNwqRJkwD8Mim1sbERf/7znxETEwObzYbCwkJIpVIu2ALAmTNncPnyZUyYMAGnT5/GunXrUFhYCJVKhVOnTiE+Ph7x8fFcBrl161aYzWbY7Xb86U9/gslkwsWLFyGXy/H6668jIyMjqGMQKswFawD/2Wef4fz58xg+fDi2b98OACFr0rhWHghi4YsC6QzFxr59+6Jv374d+pldDd1Bt5OANhlIpVIuMDz44IN48MEHceHCBaxZswb5+fmQyWS44447sGnTJhw5cgQtLS2QSCRISEjAxx9/jLi4OK7w9N5778FisUAul+P8+fMYOnQopFIppFIptm7dij179uCzzz5DZmYmvvnmG6xbtw5r1qy5ZueAYvfu3aivr8f48eOh1+thsVggkUj8NmlIpVIP05a0tDQ0NDQgIyMDTqcTJpMJ77//PvR6PV599VVs2LABX3zxBTeCZ/LkyZg2bVqnncwc6A2mG50Tkmtd8e6Gd6jVaqlGo3Gp1eqRAN4CMEaj0VTT5wD0A5AKIB3AlwAeu/rzKQAdgFcA/BXAS1f//D+NRvO6Wq0eCOAFAHEAIgGkAMgC0KjRaPqr1WqJRqPpFBeGWq1+HMDdGo3mcbVafRrAHI1G84Nard4E4Oerx/M1gK0ajeZjtVr9EoAsjUbzjFqtfgdAlUajeUWtVk8DMB9AIYCvr77fVwBe0Wg0h3ifeRrAUxqN5rBarf4AwDGNRvOuWq3eBeCvGo3mb2q1egWAGI1GE5b+VrVaXX71uMuZx/IAfKvRaG66+u//ALBKo9GMCMcauhEedGe6nRgajcZ19c9v1Gp1CRNwJVef+4l9vVqtfh9AGYBfA0gGUAmgAsBNAAYDeO/qSy8B6A1gkUaj2X/1/6oBKNRqdZRGo7GH/eCCwzQAm9RqdSyAEwDWX338PwH8Ra1WLwdwGQA1F1gB4H/UavUZACYAUWi9EdFph4MBLFar1T0BHEDrjSgdgFKj0Ry++pr/AbDq6rkdDuA3zOP7AXSYqYBGo6lQq9U2tVp9l0aj+QHADAD/6KjP70Zo0J3pXsdQq9USABIAxFtmqlarFQBUAGYDWK/RaCxXH38dgALA21df+h6AZzQaTcfozDoYarX6MwD/BSAHwN0A5gHYBmABgHK0BtEKALsAvK7RaH599f/dBGA3gCIARzUaTfbVx2UALBqNpn2yAO/rLcfVTFetVu8GsFKj0RxTq9UDAGwCQG88T2g0muCNFbrR4ejOdK9jXA20HsFWrVZHMM+7NRqNDYANwKu8//46gNUAPkBrUP4UrRlwl4NarX4KwBWNRvPtVboCGo3GBGAs85o3AXwI4GuBt3Cj9eYm9HhYoNFo8pm/j2X+fgrA0HB9bjfCj+6g28Wg0WjaBAKaEbPPaTSaOgBzrz7fmSmFUOBhAJlqtfokgCQAMWq1+iMA/9JoNB9efY0EgANAFQBWwpEJQAugHkAc5dmZx7vRjYDQHXRvAHjJiCVobY5xd/GAC41Gw/XA0sIcgBcBnFOr1f8PrfTCMwB2eONNNRqNQ61W/wutAfxjdPOp3QgS3UH3BsXVQNx2yNUNAo1GU69Wq+cA+AqtBbb/BfDm1acDLdh1oxui8f8BgffXA32Nh18AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "# 创建一个 Axes3D object\n",
    "ax = plt.axes(projection='3d')\n",
    "# 设置 3 个坐标轴的名称\n",
    "ax.set_xlabel('square')\n",
    "ax.set_ylabel('bedrooms')\n",
    "ax.set_zlabel('price')\n",
    "# 绘制 3D 散点图\n",
    "ax.scatter3D(df1['square'], df1['bedrooms'], df1['price'], c=df1['price'], cmap='Greens')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据规范化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>square</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.130010</td>\n",
       "      <td>-0.223675</td>\n",
       "      <td>0.475747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.504190</td>\n",
       "      <td>-0.223675</td>\n",
       "      <td>-0.084074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.502476</td>\n",
       "      <td>-0.223675</td>\n",
       "      <td>0.228626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.735723</td>\n",
       "      <td>-1.537767</td>\n",
       "      <td>-0.867025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.257476</td>\n",
       "      <td>1.090417</td>\n",
       "      <td>1.595389</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     square  bedrooms     price\n",
       "0  0.130010 -0.223675  0.475747\n",
       "1 -0.504190 -0.223675 -0.084074\n",
       "2  0.502476 -0.223675  0.228626\n",
       "3 -0.735723 -1.537767 -0.867025\n",
       "4  1.257476  1.090417  1.595389"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def normalize_feature(df):\n",
    "    return df.apply(lambda column: (column - column.mean()) / column.std())\n",
    "\n",
    "df = normalize_feature(df1)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<mpl_toolkits.mplot3d.art3d.Path3DCollection at 0x122f76198>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plt.axes(projection='3d')\n",
    "ax.set_xlabel('square')\n",
    "ax.set_ylabel('bedrooms')\n",
    "ax.set_zlabel('price')\n",
    "ax.scatter3D(df['square'], df['bedrooms'], df['price'], c=df['price'], cmap='Reds')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 47 entries, 0 to 46\n",
      "Data columns (total 3 columns):\n",
      "square      47 non-null float64\n",
      "bedrooms    47 non-null float64\n",
      "price       47 non-null float64\n",
      "dtypes: float64(3)\n",
      "memory usage: 1.2 KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据处理：添加 ones 列（x0）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "ones = pd.DataFrame({'ones': np.ones(len(df))})# ones是n行1列的数据框，表示x0恒为1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 47 entries, 0 to 46\n",
      "Data columns (total 1 columns):\n",
      "ones    47 non-null float64\n",
      "dtypes: float64(1)\n",
      "memory usage: 456.0 bytes\n"
     ]
    }
   ],
   "source": [
    "ones.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ones</th>\n",
       "      <th>square</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.130010</td>\n",
       "      <td>-0.223675</td>\n",
       "      <td>0.475747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.504190</td>\n",
       "      <td>-0.223675</td>\n",
       "      <td>-0.084074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.502476</td>\n",
       "      <td>-0.223675</td>\n",
       "      <td>0.228626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.735723</td>\n",
       "      <td>-1.537767</td>\n",
       "      <td>-0.867025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.257476</td>\n",
       "      <td>1.090417</td>\n",
       "      <td>1.595389</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ones    square  bedrooms     price\n",
       "0   1.0  0.130010 -0.223675  0.475747\n",
       "1   1.0 -0.504190 -0.223675 -0.084074\n",
       "2   1.0  0.502476 -0.223675  0.228626\n",
       "3   1.0 -0.735723 -1.537767 -0.867025\n",
       "4   1.0  1.257476  1.090417  1.595389"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.concat([ones, df], axis=1)  # 根据列合并数据\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 47 entries, 0 to 46\n",
      "Data columns (total 4 columns):\n",
      "ones        47 non-null float64\n",
      "square      47 non-null float64\n",
      "bedrooms    47 non-null float64\n",
      "price       47 non-null float64\n",
      "dtypes: float64(4)\n",
      "memory usage: 1.5 KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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